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{
"cell_type": "markdown",
"id": "b25a504d-d063-4edd-b471-baf566f0eb5d",
"metadata": {},
"source": [
"### Welcome\n",
"This is a very basic overview of the PANDAS Python Library. DataFrame- An object that is a table with rows and columns, created using pandas from an CSV file exported from excel, google sheets etc. THe first 3 are setup steps that you need to do all the time."
]
},
{
"cell_type": "markdown",
"id": "970940cf-99ec-4358-805e-b21d75c88e06",
"metadata": {},
"source": [
"### 1. Imports Pandas Library\n",
"pd allows us to shorten bits of code"
]
},
{
"cell_type": "code",
"execution_count": 86,
"id": "8934a04f-8ce5-4210-86ec-4e4c37ca0635",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "markdown",
"id": "4f180536-67f6-456c-9fba-0d3df229b184",
"metadata": {},
"source": [
"### 2. Set how many rows you want to display in the notebook.\n",
"We are limiting it to 100 rows in this example."
]
},
{
"cell_type": "code",
"execution_count": 87,
"id": "40d9ac9b-2d89-4f48-b52d-e224e843e37b",
"metadata": {},
"outputs": [],
"source": [
"pd.set_option('display.max_rows', 100) "
]
},
{
"cell_type": "markdown",
"id": "8d66b1b0-86b0-47a3-9f85-2372f6b5d7b5",
"metadata": {},
"source": [
"### 3. Read the CSV File\n",
"Read the csv file an asssign it to an easy to use variable name (Must be uploaded into Jupyter Lab"
]
},
{
"cell_type": "code",
"execution_count": 88,
"id": "8619daae-8c85-4995-bf62-937989e3f253",
"metadata": {},
"outputs": [],
"source": [
"pokemon = pd.read_csv(\"pokemon.csv\")"
]
},
{
"cell_type": "markdown",
"id": "aaf41db2-f687-4702-a522-b7ff9dcc8d1c",
"metadata": {},
"source": [
"### 4. Display the Data\n",
"All you need to do is type the name of the variable you created for the data set."
]
},
{
"cell_type": "code",
"execution_count": 89,
"id": "7e046b34-c437-4cde-8fac-e535cd5b1277",
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>name</th>\n",
" <th>type</th>\n",
" <th>subtype</th>\n",
" <th>total</th>\n",
" <th>hp</th>\n",
" <th>attack</th>\n",
" <th>defense</th>\n",
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" <th>0</th>\n",
" <td>Bulbasaur</td>\n",
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" <tr>\n",
" <th>2</th>\n",
" <td>Venusaur</td>\n",
" <td>Grass</td>\n",
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" <td>525</td>\n",
" <td>80</td>\n",
" <td>82</td>\n",
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" <td>100</td>\n",
" <td>100</td>\n",
" <td>80</td>\n",
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" <tr>\n",
" <th>3</th>\n",
" <td>VenusaurMega Venusaur</td>\n",
" <td>Grass</td>\n",
" <td>Poison</td>\n",
" <td>625</td>\n",
" <td>80</td>\n",
" <td>100</td>\n",
" <td>123</td>\n",
" <td>122</td>\n",
" <td>120</td>\n",
" <td>80</td>\n",
" <td>1</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Charmander</td>\n",
" <td>Fire</td>\n",
" <td>NaN</td>\n",
" <td>309</td>\n",
" <td>39</td>\n",
" <td>52</td>\n",
" <td>43</td>\n",
" <td>60</td>\n",
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" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>795</th>\n",
" <td>Diancie</td>\n",
" <td>Rock</td>\n",
" <td>Fairy</td>\n",
" <td>600</td>\n",
" <td>50</td>\n",
" <td>100</td>\n",
" <td>150</td>\n",
" <td>100</td>\n",
" <td>150</td>\n",
" <td>50</td>\n",
" <td>6</td>\n",
" <td>True</td>\n",
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" <tr>\n",
" <th>796</th>\n",
" <td>DiancieMega Diancie</td>\n",
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" <td>50</td>\n",
" <td>160</td>\n",
" <td>110</td>\n",
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" <td>True</td>\n",
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" <th>797</th>\n",
" <td>HoopaHoopa Confined</td>\n",
" <td>Psychic</td>\n",
" <td>Ghost</td>\n",
" <td>600</td>\n",
" <td>80</td>\n",
" <td>110</td>\n",
" <td>60</td>\n",
" <td>150</td>\n",
" <td>130</td>\n",
" <td>70</td>\n",
" <td>6</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>798</th>\n",
" <td>HoopaHoopa Unbound</td>\n",
" <td>Psychic</td>\n",
" <td>Dark</td>\n",
" <td>680</td>\n",
" <td>80</td>\n",
" <td>160</td>\n",
" <td>60</td>\n",
" <td>170</td>\n",
" <td>130</td>\n",
" <td>80</td>\n",
" <td>6</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>799</th>\n",
" <td>Volcanion</td>\n",
" <td>Fire</td>\n",
" <td>Water</td>\n",
" <td>600</td>\n",
" <td>80</td>\n",
" <td>110</td>\n",
" <td>120</td>\n",
" <td>130</td>\n",
" <td>90</td>\n",
" <td>70</td>\n",
" <td>6</td>\n",
" <td>True</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>800 rows × 12 columns</p>\n",
"</div>"
],
"text/plain": [
" name type subtype total hp attack defense \\\n",
"0 Bulbasaur Grass Poison 318 45 49 49 \n",
"1 Ivysaur Grass Poison 405 60 62 63 \n",
"2 Venusaur Grass Poison 525 80 82 83 \n",
"3 VenusaurMega Venusaur Grass Poison 625 80 100 123 \n",
"4 Charmander Fire NaN 309 39 52 43 \n",
".. ... ... ... ... .. ... ... \n",
"795 Diancie Rock Fairy 600 50 100 150 \n",
"796 DiancieMega Diancie Rock Fairy 700 50 160 110 \n",
"797 HoopaHoopa Confined Psychic Ghost 600 80 110 60 \n",
"798 HoopaHoopa Unbound Psychic Dark 680 80 160 60 \n",
"799 Volcanion Fire Water 600 80 110 120 \n",
"\n",
" special_attack special_defense speed generation legendary \n",
"0 65 65 45 1 False \n",
"1 80 80 60 1 False \n",
"2 100 100 80 1 False \n",
"3 122 120 80 1 False \n",
"4 60 50 65 1 False \n",
".. ... ... ... ... ... \n",
"795 100 150 50 6 True \n",
"796 160 110 110 6 True \n",
"797 150 130 70 6 True \n",
"798 170 130 80 6 True \n",
"799 130 90 70 6 True \n",
"\n",
"[800 rows x 12 columns]"
]
},
"execution_count": 89,
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"source": [
"pokemon"
]
},
{
"cell_type": "markdown",
"id": "6311f649-9d27-4c4a-bd52-7ab767cc488c",
"metadata": {},
"source": [
"---\n",
"### Acessing Specific Columns\n",
"You can access specific columns using variable name (using dot notation) followed by the name of the column, ie. `pokemon.type` as seen below. These wont be sorted."
]
},
{
"cell_type": "code",
"execution_count": 90,
"id": "59efbfe1-8106-45bb-aca8-ff3aadc59214",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0 Grass\n",
"1 Grass\n",
"2 Grass\n",
"3 Grass\n",
"4 Fire\n",
" ... \n",
"795 Rock\n",
"796 Rock\n",
"797 Psychic\n",
"798 Psychic\n",
"799 Fire\n",
"Name: type, Length: 800, dtype: object"
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"execution_count": 90,
"metadata": {},
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"source": [
"pokemon.type"
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},
{
"cell_type": "markdown",
"id": "07639e29-633c-4975-b5c1-4f5a2bcb2d4d",
"metadata": {},
"source": [
"---\n",
"### Descriptive Methods\n",
"Below will contain several Pandas Descriptive Methods that are useful for sorting / categorizing / Analyzing Data.\n"
]
},
{
"cell_type": "markdown",
"id": "64a20f07-c087-4e65-a71c-e6df8bde679b",
"metadata": {},
"source": [
"### value_counts()\n",
"Tells you how many of each data is in a column. Use: `series.column_name.value_counts()`. In the example below the count of all the different types are shown from the \"type\" column, there are 112 pokemon with the \"Water\" type."
]
},
{
"cell_type": "code",
"execution_count": 91,
"id": "e5ab1739-0139-439f-ac8d-ffb91f14764f",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"type\n",
"Water 112\n",
"Normal 98\n",
"Grass 70\n",
"Bug 69\n",
"Psychic 57\n",
"Fire 52\n",
"Rock 44\n",
"Electric 44\n",
"Ground 32\n",
"Ghost 32\n",
"Dragon 32\n",
"Dark 31\n",
"Poison 28\n",
"Fighting 27\n",
"Steel 27\n",
"Ice 24\n",
"Fairy 17\n",
"Flying 4\n",
"Name: count, dtype: int64"
]
},
"execution_count": 91,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pokemon.type.value_counts()"
]
},
{
"cell_type": "markdown",
"id": "6cab1efa-8da6-4807-a6a7-18ff78b6b409",
"metadata": {},
"source": [
"### mean()\n",
"Gets the mean of an entire column. Use: `series.column.mean()`. Access multiple columns using: `series[[\"column_name1\", \"column_name2\", \"column_name3\"]].mean()`\n",
"\n",
"-You can also compute the mean of a a Boolean Column (uses true or false instead of a number), True will map to 1 and False to 0. Therefore the % tells you what percent is true. Use: `series.column.mean() * 100`"
]
},
{
"cell_type": "code",
"execution_count": 92,
"id": "cb997fc1-becc-4323-810c-3392c7ada17a",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"69.25875"
]
},
"execution_count": 92,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pokemon.hp.mean()"
]
},
{
"cell_type": "code",
"execution_count": 93,
"id": "e90148bd-efde-4673-b9ef-c66c301d0ff1",
"metadata": {},
"outputs": [
{
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" <td>50</td>\n",
" <td>160</td>\n",
" <td>110</td>\n",
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" <tr>\n",
" <th>797</th>\n",
" <td>80</td>\n",
" <td>110</td>\n",
" <td>60</td>\n",
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" <tr>\n",
" <th>798</th>\n",
" <td>80</td>\n",
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" <th>799</th>\n",
" <td>80</td>\n",
" <td>110</td>\n",
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"<p>800 rows × 3 columns</p>\n",
"</div>"
],
"text/plain": [
" hp attack defense\n",
"0 45 49 49\n",
"1 60 62 63\n",
"2 80 82 83\n",
"3 80 100 123\n",
"4 39 52 43\n",
".. .. ... ...\n",
"795 50 100 150\n",
"796 50 160 110\n",
"797 80 110 60\n",
"798 80 160 60\n",
"799 80 110 120\n",
"\n",
"[800 rows x 3 columns]"
]
},
"execution_count": 93,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pokemon[[\"hp\", \"attack\", \"defense\"]]"
]
},
{
"cell_type": "code",
"execution_count": 94,
"id": "c3b88a48-69a0-47d2-8fc8-f5ff4f4d7bd7",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"8.125"
]
},
"execution_count": 94,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pokemon.legendary.mean()*100"
]
},
{
"cell_type": "markdown",
"id": "6f1cb533-8a84-4211-83da-a914ecd5ecc8",
"metadata": {},
"source": [
"### sort_values()\n",
"Allows for sorting of data. Use: `series.sort_values(\"column you want to sort by\")`"
]
},
{
"cell_type": "code",
"execution_count": 95,
"id": "2cd3d37b-bff5-46da-81dc-b3387de7a183",
"metadata": {},
"outputs": [
{
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" <tr>\n",
" <th>381</th>\n",
" <td>Feebas</td>\n",
" <td>Water</td>\n",
" <td>NaN</td>\n",
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" <td>20</td>\n",
" <td>15</td>\n",
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" <td>15</td>\n",
" <td>20</td>\n",
" <td>80</td>\n",
" <td>1</td>\n",
" <td>False</td>\n",
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" <tr>\n",
" <th>388</th>\n",
" <td>Duskull</td>\n",
" <td>Ghost</td>\n",
" <td>NaN</td>\n",
" <td>295</td>\n",
" <td>20</td>\n",
" <td>40</td>\n",
" <td>90</td>\n",
" <td>30</td>\n",
" <td>90</td>\n",
" <td>25</td>\n",
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" <td>Alomomola</td>\n",
" <td>Water</td>\n",
" <td>NaN</td>\n",
" <td>470</td>\n",
" <td>165</td>\n",
" <td>75</td>\n",
" <td>80</td>\n",
" <td>40</td>\n",
" <td>45</td>\n",
" <td>65</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>351</th>\n",
" <td>Wailord</td>\n",
" <td>Water</td>\n",
" <td>NaN</td>\n",
" <td>500</td>\n",
" <td>170</td>\n",
" <td>90</td>\n",
" <td>45</td>\n",
" <td>90</td>\n",
" <td>45</td>\n",
" <td>60</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>217</th>\n",
" <td>Wobbuffet</td>\n",
" <td>Psychic</td>\n",
" <td>NaN</td>\n",
" <td>405</td>\n",
" <td>190</td>\n",
" <td>33</td>\n",
" <td>58</td>\n",
" <td>33</td>\n",
" <td>58</td>\n",
" <td>33</td>\n",
" <td>2</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>121</th>\n",
" <td>Chansey</td>\n",
" <td>Normal</td>\n",
" <td>NaN</td>\n",
" <td>450</td>\n",
" <td>250</td>\n",
" <td>5</td>\n",
" <td>5</td>\n",
" <td>35</td>\n",
" <td>105</td>\n",
" <td>50</td>\n",
" <td>1</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>261</th>\n",
" <td>Blissey</td>\n",
" <td>Normal</td>\n",
" <td>NaN</td>\n",
" <td>540</td>\n",
" <td>255</td>\n",
" <td>10</td>\n",
" <td>10</td>\n",
" <td>75</td>\n",
" <td>135</td>\n",
" <td>55</td>\n",
" <td>2</td>\n",
" <td>False</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>800 rows × 12 columns</p>\n",
"</div>"
],
"text/plain": [
" name type subtype total hp attack defense special_attack \\\n",
"316 Shedinja Bug Ghost 236 1 90 45 30 \n",
"55 Diglett Ground NaN 265 10 55 25 35 \n",
"381 Feebas Water NaN 200 20 15 20 10 \n",
"139 Magikarp Water NaN 200 20 10 55 15 \n",
"388 Duskull Ghost NaN 295 20 40 90 30 \n",
".. ... ... ... ... ... ... ... ... \n",
"655 Alomomola Water NaN 470 165 75 80 40 \n",
"351 Wailord Water NaN 500 170 90 45 90 \n",
"217 Wobbuffet Psychic NaN 405 190 33 58 33 \n",
"121 Chansey Normal NaN 450 250 5 5 35 \n",
"261 Blissey Normal NaN 540 255 10 10 75 \n",
"\n",
" special_defense speed generation legendary \n",
"316 30 40 3 False \n",
"55 45 95 1 False \n",
"381 55 80 3 False \n",
"139 20 80 1 False \n",
"388 90 25 3 False \n",
".. ... ... ... ... \n",
"655 45 65 5 False \n",
"351 45 60 3 False \n",
"217 58 33 2 False \n",
"121 105 50 1 False \n",
"261 135 55 2 False \n",
"\n",
"[800 rows x 12 columns]"
]
},
"execution_count": 95,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pokemon.sort_values(\"hp\")"
]
},
{
"cell_type": "markdown",
"id": "fd1f5807-a8bd-4e34-a14a-89a53832530f",
"metadata": {},
"source": [
"___\n",
"### Filtering Methods\n",
"Filtering out columns gives great flexibility in how we use data. Below are some common uses."
]
},
{
"cell_type": "markdown",
"id": "d4bea759-474d-470e-b96d-a67d841b83fe",
"metadata": {},
"source": [
"### Filtering a Boolean Column\n",
"To filter a Boolean column you should first create a variable that contains: `variable = series[series.column]. Simply call the variable, since they are a boolean value, it will sort to show you the \"True\" values by default. Note that it also shows ALL columns that correspond to the \"True\" in the legendary column."
]
},
{
"cell_type": "code",
"execution_count": 96,
"id": "27271172-0e17-4734-931e-10bb87478c0a",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
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"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>name</th>\n",
" <th>type</th>\n",
" <th>subtype</th>\n",
" <th>total</th>\n",
" <th>hp</th>\n",
" <th>attack</th>\n",
" <th>defense</th>\n",
" <th>special_attack</th>\n",
" <th>special_defense</th>\n",
" <th>speed</th>\n",
" <th>generation</th>\n",
" <th>legendary</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>156</th>\n",
" <td>Articuno</td>\n",
" <td>Ice</td>\n",
" <td>Flying</td>\n",
" <td>580</td>\n",
" <td>90</td>\n",
" <td>85</td>\n",
" <td>100</td>\n",
" <td>95</td>\n",
" <td>125</td>\n",
" <td>85</td>\n",
" <td>1</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>157</th>\n",
" <td>Zapdos</td>\n",
" <td>Electric</td>\n",
" <td>Flying</td>\n",
" <td>580</td>\n",
" <td>90</td>\n",
" <td>90</td>\n",
" <td>85</td>\n",
" <td>125</td>\n",
" <td>90</td>\n",
" <td>100</td>\n",
" <td>1</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>158</th>\n",
" <td>Moltres</td>\n",
" <td>Fire</td>\n",
" <td>Flying</td>\n",
" <td>580</td>\n",
" <td>90</td>\n",
" <td>100</td>\n",
" <td>90</td>\n",
" <td>125</td>\n",
" <td>85</td>\n",
" <td>90</td>\n",
" <td>1</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>162</th>\n",
" <td>Mewtwo</td>\n",
" <td>Psychic</td>\n",
" <td>NaN</td>\n",
" <td>680</td>\n",
" <td>106</td>\n",
" <td>110</td>\n",
" <td>90</td>\n",
" <td>154</td>\n",
" <td>90</td>\n",
" <td>130</td>\n",
" <td>1</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>163</th>\n",
" <td>MewtwoMega Mewtwo X</td>\n",
" <td>Psychic</td>\n",
" <td>Fighting</td>\n",
" <td>780</td>\n",
" <td>106</td>\n",
" <td>190</td>\n",
" <td>100</td>\n",
" <td>154</td>\n",
" <td>100</td>\n",
" <td>130</td>\n",
" <td>1</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>164</th>\n",
" <td>MewtwoMega Mewtwo Y</td>\n",
" <td>Psychic</td>\n",
" <td>NaN</td>\n",
" <td>780</td>\n",
" <td>106</td>\n",
" <td>150</td>\n",
" <td>70</td>\n",
" <td>194</td>\n",
" <td>120</td>\n",
" <td>140</td>\n",
" <td>1</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>262</th>\n",
" <td>Raikou</td>\n",
" <td>Electric</td>\n",
" <td>NaN</td>\n",
" <td>580</td>\n",
" <td>90</td>\n",
" <td>85</td>\n",
" <td>75</td>\n",
" <td>115</td>\n",
" <td>100</td>\n",
" <td>115</td>\n",
" <td>2</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>263</th>\n",
" <td>Entei</td>\n",
" <td>Fire</td>\n",
" <td>NaN</td>\n",
" <td>580</td>\n",
" <td>115</td>\n",
" <td>115</td>\n",
" <td>85</td>\n",
" <td>90</td>\n",
" <td>75</td>\n",
" <td>100</td>\n",
" <td>2</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>264</th>\n",
" <td>Suicune</td>\n",
" <td>Water</td>\n",
" <td>NaN</td>\n",
" <td>580</td>\n",
" <td>100</td>\n",
" <td>75</td>\n",
" <td>115</td>\n",
" <td>90</td>\n",
" <td>115</td>\n",
" <td>85</td>\n",
" <td>2</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>269</th>\n",
" <td>Lugia</td>\n",
" <td>Psychic</td>\n",
" <td>Flying</td>\n",
" <td>680</td>\n",
" <td>106</td>\n",
" <td>90</td>\n",
" <td>130</td>\n",
" <td>90</td>\n",
" <td>154</td>\n",
" <td>110</td>\n",
" <td>2</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>270</th>\n",
" <td>Ho-oh</td>\n",
" <td>Fire</td>\n",
" <td>Flying</td>\n",
" <td>680</td>\n",
" <td>106</td>\n",
" <td>130</td>\n",
" <td>90</td>\n",
" <td>110</td>\n",
" <td>154</td>\n",
" <td>90</td>\n",
" <td>2</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>414</th>\n",
" <td>Regirock</td>\n",
" <td>Rock</td>\n",
" <td>NaN</td>\n",
" <td>580</td>\n",
" <td>80</td>\n",
" <td>100</td>\n",
" <td>200</td>\n",
" <td>50</td>\n",
" <td>100</td>\n",
" <td>50</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>415</th>\n",
" <td>Regice</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>580</td>\n",
" <td>80</td>\n",
" <td>50</td>\n",
" <td>100</td>\n",
" <td>100</td>\n",
" <td>200</td>\n",
" <td>50</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>416</th>\n",
" <td>Registeel</td>\n",
" <td>Steel</td>\n",
" <td>NaN</td>\n",
" <td>580</td>\n",
" <td>80</td>\n",
" <td>75</td>\n",
" <td>150</td>\n",
" <td>75</td>\n",
" <td>150</td>\n",
" <td>50</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>417</th>\n",
" <td>Latias</td>\n",
" <td>Dragon</td>\n",
" <td>Psychic</td>\n",
" <td>600</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
" <td>90</td>\n",
" <td>110</td>\n",
" <td>130</td>\n",
" <td>110</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>418</th>\n",
" <td>LatiasMega Latias</td>\n",
" <td>Dragon</td>\n",
" <td>Psychic</td>\n",
" <td>700</td>\n",
" <td>80</td>\n",
" <td>100</td>\n",
" <td>120</td>\n",
" <td>140</td>\n",
" <td>150</td>\n",
" <td>110</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>419</th>\n",
" <td>Latios</td>\n",
" <td>Dragon</td>\n",
" <td>Psychic</td>\n",
" <td>600</td>\n",
" <td>80</td>\n",
" <td>90</td>\n",
" <td>80</td>\n",
" <td>130</td>\n",
" <td>110</td>\n",
" <td>110</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>420</th>\n",
" <td>LatiosMega Latios</td>\n",
" <td>Dragon</td>\n",
" <td>Psychic</td>\n",
" <td>700</td>\n",
" <td>80</td>\n",
" <td>130</td>\n",
" <td>100</td>\n",
" <td>160</td>\n",
" <td>120</td>\n",
" <td>110</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>421</th>\n",
" <td>Kyogre</td>\n",
" <td>Water</td>\n",
" <td>NaN</td>\n",
" <td>670</td>\n",
" <td>100</td>\n",
" <td>100</td>\n",
" <td>90</td>\n",
" <td>150</td>\n",
" <td>140</td>\n",
" <td>90</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>422</th>\n",
" <td>KyogrePrimal Kyogre</td>\n",
" <td>Water</td>\n",
" <td>NaN</td>\n",
" <td>770</td>\n",
" <td>100</td>\n",
" <td>150</td>\n",
" <td>90</td>\n",
" <td>180</td>\n",
" <td>160</td>\n",
" <td>90</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>423</th>\n",
" <td>Groudon</td>\n",
" <td>Ground</td>\n",
" <td>NaN</td>\n",
" <td>670</td>\n",
" <td>100</td>\n",
" <td>150</td>\n",
" <td>140</td>\n",
" <td>100</td>\n",
" <td>90</td>\n",
" <td>90</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>424</th>\n",
" <td>GroudonPrimal Groudon</td>\n",
" <td>Ground</td>\n",
" <td>Fire</td>\n",
" <td>770</td>\n",
" <td>100</td>\n",
" <td>180</td>\n",
" <td>160</td>\n",
" <td>150</td>\n",
" <td>90</td>\n",
" <td>90</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>425</th>\n",
" <td>Rayquaza</td>\n",
" <td>Dragon</td>\n",
" <td>Flying</td>\n",
" <td>680</td>\n",
" <td>105</td>\n",
" <td>150</td>\n",
" <td>90</td>\n",
" <td>150</td>\n",
" <td>90</td>\n",
" <td>95</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>426</th>\n",
" <td>RayquazaMega Rayquaza</td>\n",
" <td>Dragon</td>\n",
" <td>Flying</td>\n",
" <td>780</td>\n",
" <td>105</td>\n",
" <td>180</td>\n",
" <td>100</td>\n",
" <td>180</td>\n",
" <td>100</td>\n",
" <td>115</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>427</th>\n",
" <td>Jirachi</td>\n",
" <td>Steel</td>\n",
" <td>Psychic</td>\n",
" <td>600</td>\n",
" <td>100</td>\n",
" <td>100</td>\n",
" <td>100</td>\n",
" <td>100</td>\n",
" <td>100</td>\n",
" <td>100</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>428</th>\n",
" <td>DeoxysNormal Forme</td>\n",
" <td>Psychic</td>\n",
" <td>NaN</td>\n",
" <td>600</td>\n",
" <td>50</td>\n",
" <td>150</td>\n",
" <td>50</td>\n",
" <td>150</td>\n",
" <td>50</td>\n",
" <td>150</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>429</th>\n",
" <td>DeoxysAttack Forme</td>\n",
" <td>Psychic</td>\n",
" <td>NaN</td>\n",
" <td>600</td>\n",
" <td>50</td>\n",
" <td>180</td>\n",
" <td>20</td>\n",
" <td>180</td>\n",
" <td>20</td>\n",
" <td>150</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>430</th>\n",
" <td>DeoxysDefense Forme</td>\n",
" <td>Psychic</td>\n",
" <td>NaN</td>\n",
" <td>600</td>\n",
" <td>50</td>\n",
" <td>70</td>\n",
" <td>160</td>\n",
" <td>70</td>\n",
" <td>160</td>\n",
" <td>90</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>431</th>\n",
" <td>DeoxysSpeed Forme</td>\n",
" <td>Psychic</td>\n",
" <td>NaN</td>\n",
" <td>600</td>\n",
" <td>50</td>\n",
" <td>95</td>\n",
" <td>90</td>\n",
" <td>95</td>\n",
" <td>90</td>\n",
" <td>180</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>537</th>\n",
" <td>Uxie</td>\n",
" <td>Psychic</td>\n",
" <td>NaN</td>\n",
" <td>580</td>\n",
" <td>75</td>\n",
" <td>75</td>\n",
" <td>130</td>\n",
" <td>75</td>\n",
" <td>130</td>\n",
" <td>95</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>538</th>\n",
" <td>Mesprit</td>\n",
" <td>Psychic</td>\n",
" <td>NaN</td>\n",
" <td>580</td>\n",
" <td>80</td>\n",
" <td>105</td>\n",
" <td>105</td>\n",
" <td>105</td>\n",
" <td>105</td>\n",
" <td>80</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>539</th>\n",
" <td>Azelf</td>\n",
" <td>Psychic</td>\n",
" <td>NaN</td>\n",
" <td>580</td>\n",
" <td>75</td>\n",
" <td>125</td>\n",
" <td>70</td>\n",
" <td>125</td>\n",
" <td>70</td>\n",
" <td>115</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>540</th>\n",
" <td>Dialga</td>\n",
" <td>Steel</td>\n",
" <td>Dragon</td>\n",
" <td>680</td>\n",
" <td>100</td>\n",
" <td>120</td>\n",
" <td>120</td>\n",
" <td>150</td>\n",
" <td>100</td>\n",
" <td>90</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>541</th>\n",
" <td>Palkia</td>\n",
" <td>Water</td>\n",
" <td>Dragon</td>\n",
" <td>680</td>\n",
" <td>90</td>\n",
" <td>120</td>\n",
" <td>100</td>\n",
" <td>150</td>\n",
" <td>120</td>\n",
" <td>100</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>542</th>\n",
" <td>Heatran</td>\n",
" <td>Fire</td>\n",
" <td>Steel</td>\n",
" <td>600</td>\n",
" <td>91</td>\n",
" <td>90</td>\n",
" <td>106</td>\n",
" <td>130</td>\n",
" <td>106</td>\n",
" <td>77</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>543</th>\n",
" <td>Regigigas</td>\n",
" <td>Normal</td>\n",
" <td>NaN</td>\n",
" <td>670</td>\n",
" <td>110</td>\n",
" <td>160</td>\n",
" <td>110</td>\n",
" <td>80</td>\n",
" <td>110</td>\n",
" <td>100</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>544</th>\n",
" <td>GiratinaAltered Forme</td>\n",
" <td>Ghost</td>\n",
" <td>Dragon</td>\n",
" <td>680</td>\n",
" <td>150</td>\n",
" <td>100</td>\n",
" <td>120</td>\n",
" <td>100</td>\n",
" <td>120</td>\n",
" <td>90</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>545</th>\n",
" <td>GiratinaOrigin Forme</td>\n",
" <td>Ghost</td>\n",
" <td>Dragon</td>\n",
" <td>680</td>\n",
" <td>150</td>\n",
" <td>120</td>\n",
" <td>100</td>\n",
" <td>120</td>\n",
" <td>100</td>\n",
" <td>90</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>549</th>\n",
" <td>Darkrai</td>\n",
" <td>Dark</td>\n",
" <td>NaN</td>\n",
" <td>600</td>\n",
" <td>70</td>\n",
" <td>90</td>\n",
" <td>90</td>\n",
" <td>135</td>\n",
" <td>90</td>\n",
" <td>125</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>550</th>\n",
" <td>ShayminLand Forme</td>\n",
" <td>Grass</td>\n",
" <td>NaN</td>\n",
" <td>600</td>\n",
" <td>100</td>\n",
" <td>100</td>\n",
" <td>100</td>\n",
" <td>100</td>\n",
" <td>100</td>\n",
" <td>100</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>551</th>\n",
" <td>ShayminSky Forme</td>\n",
" <td>Grass</td>\n",
" <td>Flying</td>\n",
" <td>600</td>\n",
" <td>100</td>\n",
" <td>103</td>\n",
" <td>75</td>\n",
" <td>120</td>\n",
" <td>75</td>\n",
" <td>127</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>552</th>\n",
" <td>Arceus</td>\n",
" <td>Normal</td>\n",
" <td>NaN</td>\n",
" <td>720</td>\n",
" <td>120</td>\n",
" <td>120</td>\n",
" <td>120</td>\n",
" <td>120</td>\n",
" <td>120</td>\n",
" <td>120</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>553</th>\n",
" <td>Victini</td>\n",
" <td>Psychic</td>\n",
" <td>Fire</td>\n",
" <td>600</td>\n",
" <td>100</td>\n",
" <td>100</td>\n",
" <td>100</td>\n",
" <td>100</td>\n",
" <td>100</td>\n",
" <td>100</td>\n",
" <td>5</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>699</th>\n",
" <td>Cobalion</td>\n",
" <td>Steel</td>\n",
" <td>Fighting</td>\n",
" <td>580</td>\n",
" <td>91</td>\n",
" <td>90</td>\n",
" <td>129</td>\n",
" <td>90</td>\n",
" <td>72</td>\n",
" <td>108</td>\n",
" <td>5</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>700</th>\n",
" <td>Terrakion</td>\n",
" <td>Rock</td>\n",
" <td>Fighting</td>\n",
" <td>580</td>\n",
" <td>91</td>\n",
" <td>129</td>\n",
" <td>90</td>\n",
" <td>72</td>\n",
" <td>90</td>\n",
" <td>108</td>\n",
" <td>5</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>701</th>\n",
" <td>Virizion</td>\n",
" <td>Grass</td>\n",
" <td>Fighting</td>\n",
" <td>580</td>\n",
" <td>91</td>\n",
" <td>90</td>\n",
" <td>72</td>\n",
" <td>90</td>\n",
" <td>129</td>\n",
" <td>108</td>\n",
" <td>5</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>702</th>\n",
" <td>TornadusIncarnate Forme</td>\n",
" <td>Flying</td>\n",
" <td>NaN</td>\n",
" <td>580</td>\n",
" <td>79</td>\n",
" <td>115</td>\n",
" <td>70</td>\n",
" <td>125</td>\n",
" <td>80</td>\n",
" <td>111</td>\n",
" <td>5</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>703</th>\n",
" <td>TornadusTherian Forme</td>\n",
" <td>Flying</td>\n",
" <td>NaN</td>\n",
" <td>580</td>\n",
" <td>79</td>\n",
" <td>100</td>\n",
" <td>80</td>\n",
" <td>110</td>\n",
" <td>90</td>\n",
" <td>121</td>\n",
" <td>5</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>704</th>\n",
" <td>ThundurusIncarnate Forme</td>\n",
" <td>Electric</td>\n",
" <td>Flying</td>\n",
" <td>580</td>\n",
" <td>79</td>\n",
" <td>115</td>\n",
" <td>70</td>\n",
" <td>125</td>\n",
" <td>80</td>\n",
" <td>111</td>\n",
" <td>5</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>705</th>\n",
" <td>ThundurusTherian Forme</td>\n",
" <td>Electric</td>\n",
" <td>Flying</td>\n",
" <td>580</td>\n",
" <td>79</td>\n",
" <td>105</td>\n",
" <td>70</td>\n",
" <td>145</td>\n",
" <td>80</td>\n",
" <td>101</td>\n",
" <td>5</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>706</th>\n",
" <td>Reshiram</td>\n",
" <td>Dragon</td>\n",
" <td>Fire</td>\n",
" <td>680</td>\n",
" <td>100</td>\n",
" <td>120</td>\n",
" <td>100</td>\n",
" <td>150</td>\n",
" <td>120</td>\n",
" <td>90</td>\n",
" <td>5</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>707</th>\n",
" <td>Zekrom</td>\n",
" <td>Dragon</td>\n",
" <td>Electric</td>\n",
" <td>680</td>\n",
" <td>100</td>\n",
" <td>150</td>\n",
" <td>120</td>\n",
" <td>120</td>\n",
" <td>100</td>\n",
" <td>90</td>\n",
" <td>5</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>708</th>\n",
" <td>LandorusIncarnate Forme</td>\n",
" <td>Ground</td>\n",
" <td>Flying</td>\n",
" <td>600</td>\n",
" <td>89</td>\n",
" <td>125</td>\n",
" <td>90</td>\n",
" <td>115</td>\n",
" <td>80</td>\n",
" <td>101</td>\n",
" <td>5</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>709</th>\n",
" <td>LandorusTherian Forme</td>\n",
" <td>Ground</td>\n",
" <td>Flying</td>\n",
" <td>600</td>\n",
" <td>89</td>\n",
" <td>145</td>\n",
" <td>90</td>\n",
" <td>105</td>\n",
" <td>80</td>\n",
" <td>91</td>\n",
" <td>5</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>710</th>\n",
" <td>Kyurem</td>\n",
" <td>Dragon</td>\n",
" <td>Ice</td>\n",
" <td>660</td>\n",
" <td>125</td>\n",
" <td>130</td>\n",
" <td>90</td>\n",
" <td>130</td>\n",
" <td>90</td>\n",
" <td>95</td>\n",
" <td>5</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>711</th>\n",
" <td>KyuremBlack Kyurem</td>\n",
" <td>Dragon</td>\n",
" <td>Ice</td>\n",
" <td>700</td>\n",
" <td>125</td>\n",
" <td>170</td>\n",
" <td>100</td>\n",
" <td>120</td>\n",
" <td>90</td>\n",
" <td>95</td>\n",
" <td>5</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>712</th>\n",
" <td>KyuremWhite Kyurem</td>\n",
" <td>Dragon</td>\n",
" <td>Ice</td>\n",
" <td>700</td>\n",
" <td>125</td>\n",
" <td>120</td>\n",
" <td>90</td>\n",
" <td>170</td>\n",
" <td>100</td>\n",
" <td>95</td>\n",
" <td>5</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>792</th>\n",
" <td>Xerneas</td>\n",
" <td>Fairy</td>\n",
" <td>NaN</td>\n",
" <td>680</td>\n",
" <td>126</td>\n",
" <td>131</td>\n",
" <td>95</td>\n",
" <td>131</td>\n",
" <td>98</td>\n",
" <td>99</td>\n",
" <td>6</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>793</th>\n",
" <td>Yveltal</td>\n",
" <td>Dark</td>\n",
" <td>Flying</td>\n",
" <td>680</td>\n",
" <td>126</td>\n",
" <td>131</td>\n",
" <td>95</td>\n",
" <td>131</td>\n",
" <td>98</td>\n",
" <td>99</td>\n",
" <td>6</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>794</th>\n",
" <td>Zygarde50% Forme</td>\n",
" <td>Dragon</td>\n",
" <td>Ground</td>\n",
" <td>600</td>\n",
" <td>108</td>\n",
" <td>100</td>\n",
" <td>121</td>\n",
" <td>81</td>\n",
" <td>95</td>\n",
" <td>95</td>\n",
" <td>6</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>795</th>\n",
" <td>Diancie</td>\n",
" <td>Rock</td>\n",
" <td>Fairy</td>\n",
" <td>600</td>\n",
" <td>50</td>\n",
" <td>100</td>\n",
" <td>150</td>\n",
" <td>100</td>\n",
" <td>150</td>\n",
" <td>50</td>\n",
" <td>6</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>796</th>\n",
" <td>DiancieMega Diancie</td>\n",
" <td>Rock</td>\n",
" <td>Fairy</td>\n",
" <td>700</td>\n",
" <td>50</td>\n",
" <td>160</td>\n",
" <td>110</td>\n",
" <td>160</td>\n",
" <td>110</td>\n",
" <td>110</td>\n",
" <td>6</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>797</th>\n",
" <td>HoopaHoopa Confined</td>\n",
" <td>Psychic</td>\n",
" <td>Ghost</td>\n",
" <td>600</td>\n",
" <td>80</td>\n",
" <td>110</td>\n",
" <td>60</td>\n",
" <td>150</td>\n",
" <td>130</td>\n",
" <td>70</td>\n",
" <td>6</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>798</th>\n",
" <td>HoopaHoopa Unbound</td>\n",
" <td>Psychic</td>\n",
" <td>Dark</td>\n",
" <td>680</td>\n",
" <td>80</td>\n",
" <td>160</td>\n",
" <td>60</td>\n",
" <td>170</td>\n",
" <td>130</td>\n",
" <td>80</td>\n",
" <td>6</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>799</th>\n",
" <td>Volcanion</td>\n",
" <td>Fire</td>\n",
" <td>Water</td>\n",
" <td>600</td>\n",
" <td>80</td>\n",
" <td>110</td>\n",
" <td>120</td>\n",
" <td>130</td>\n",
" <td>90</td>\n",
" <td>70</td>\n",
" <td>6</td>\n",
" <td>True</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" name type subtype total hp attack \\\n",
"156 Articuno Ice Flying 580 90 85 \n",
"157 Zapdos Electric Flying 580 90 90 \n",
"158 Moltres Fire Flying 580 90 100 \n",
"162 Mewtwo Psychic NaN 680 106 110 \n",
"163 MewtwoMega Mewtwo X Psychic Fighting 780 106 190 \n",
"164 MewtwoMega Mewtwo Y Psychic NaN 780 106 150 \n",
"262 Raikou Electric NaN 580 90 85 \n",
"263 Entei Fire NaN 580 115 115 \n",
"264 Suicune Water NaN 580 100 75 \n",
"269 Lugia Psychic Flying 680 106 90 \n",
"270 Ho-oh Fire Flying 680 106 130 \n",
"414 Regirock Rock NaN 580 80 100 \n",
"415 Regice Ice NaN 580 80 50 \n",
"416 Registeel Steel NaN 580 80 75 \n",
"417 Latias Dragon Psychic 600 80 80 \n",
"418 LatiasMega Latias Dragon Psychic 700 80 100 \n",
"419 Latios Dragon Psychic 600 80 90 \n",
"420 LatiosMega Latios Dragon Psychic 700 80 130 \n",
"421 Kyogre Water NaN 670 100 100 \n",
"422 KyogrePrimal Kyogre Water NaN 770 100 150 \n",
"423 Groudon Ground NaN 670 100 150 \n",
"424 GroudonPrimal Groudon Ground Fire 770 100 180 \n",
"425 Rayquaza Dragon Flying 680 105 150 \n",
"426 RayquazaMega Rayquaza Dragon Flying 780 105 180 \n",
"427 Jirachi Steel Psychic 600 100 100 \n",
"428 DeoxysNormal Forme Psychic NaN 600 50 150 \n",
"429 DeoxysAttack Forme Psychic NaN 600 50 180 \n",
"430 DeoxysDefense Forme Psychic NaN 600 50 70 \n",
"431 DeoxysSpeed Forme Psychic NaN 600 50 95 \n",
"537 Uxie Psychic NaN 580 75 75 \n",
"538 Mesprit Psychic NaN 580 80 105 \n",
"539 Azelf Psychic NaN 580 75 125 \n",
"540 Dialga Steel Dragon 680 100 120 \n",
"541 Palkia Water Dragon 680 90 120 \n",
"542 Heatran Fire Steel 600 91 90 \n",
"543 Regigigas Normal NaN 670 110 160 \n",
"544 GiratinaAltered Forme Ghost Dragon 680 150 100 \n",
"545 GiratinaOrigin Forme Ghost Dragon 680 150 120 \n",
"549 Darkrai Dark NaN 600 70 90 \n",
"550 ShayminLand Forme Grass NaN 600 100 100 \n",
"551 ShayminSky Forme Grass Flying 600 100 103 \n",
"552 Arceus Normal NaN 720 120 120 \n",
"553 Victini Psychic Fire 600 100 100 \n",
"699 Cobalion Steel Fighting 580 91 90 \n",
"700 Terrakion Rock Fighting 580 91 129 \n",
"701 Virizion Grass Fighting 580 91 90 \n",
"702 TornadusIncarnate Forme Flying NaN 580 79 115 \n",
"703 TornadusTherian Forme Flying NaN 580 79 100 \n",
"704 ThundurusIncarnate Forme Electric Flying 580 79 115 \n",
"705 ThundurusTherian Forme Electric Flying 580 79 105 \n",
"706 Reshiram Dragon Fire 680 100 120 \n",
"707 Zekrom Dragon Electric 680 100 150 \n",
"708 LandorusIncarnate Forme Ground Flying 600 89 125 \n",
"709 LandorusTherian Forme Ground Flying 600 89 145 \n",
"710 Kyurem Dragon Ice 660 125 130 \n",
"711 KyuremBlack Kyurem Dragon Ice 700 125 170 \n",
"712 KyuremWhite Kyurem Dragon Ice 700 125 120 \n",
"792 Xerneas Fairy NaN 680 126 131 \n",
"793 Yveltal Dark Flying 680 126 131 \n",
"794 Zygarde50% Forme Dragon Ground 600 108 100 \n",
"795 Diancie Rock Fairy 600 50 100 \n",
"796 DiancieMega Diancie Rock Fairy 700 50 160 \n",
"797 HoopaHoopa Confined Psychic Ghost 600 80 110 \n",
"798 HoopaHoopa Unbound Psychic Dark 680 80 160 \n",
"799 Volcanion Fire Water 600 80 110 \n",
"\n",
" defense special_attack special_defense speed generation legendary \n",
"156 100 95 125 85 1 True \n",
"157 85 125 90 100 1 True \n",
"158 90 125 85 90 1 True \n",
"162 90 154 90 130 1 True \n",
"163 100 154 100 130 1 True \n",
"164 70 194 120 140 1 True \n",
"262 75 115 100 115 2 True \n",
"263 85 90 75 100 2 True \n",
"264 115 90 115 85 2 True \n",
"269 130 90 154 110 2 True \n",
"270 90 110 154 90 2 True \n",
"414 200 50 100 50 3 True \n",
"415 100 100 200 50 3 True \n",
"416 150 75 150 50 3 True \n",
"417 90 110 130 110 3 True \n",
"418 120 140 150 110 3 True \n",
"419 80 130 110 110 3 True \n",
"420 100 160 120 110 3 True \n",
"421 90 150 140 90 3 True \n",
"422 90 180 160 90 3 True \n",
"423 140 100 90 90 3 True \n",
"424 160 150 90 90 3 True \n",
"425 90 150 90 95 3 True \n",
"426 100 180 100 115 3 True \n",
"427 100 100 100 100 3 True \n",
"428 50 150 50 150 3 True \n",
"429 20 180 20 150 3 True \n",
"430 160 70 160 90 3 True \n",
"431 90 95 90 180 3 True \n",
"537 130 75 130 95 4 True \n",
"538 105 105 105 80 4 True \n",
"539 70 125 70 115 4 True \n",
"540 120 150 100 90 4 True \n",
"541 100 150 120 100 4 True \n",
"542 106 130 106 77 4 True \n",
"543 110 80 110 100 4 True \n",
"544 120 100 120 90 4 True \n",
"545 100 120 100 90 4 True \n",
"549 90 135 90 125 4 True \n",
"550 100 100 100 100 4 True \n",
"551 75 120 75 127 4 True \n",
"552 120 120 120 120 4 True \n",
"553 100 100 100 100 5 True \n",
"699 129 90 72 108 5 True \n",
"700 90 72 90 108 5 True \n",
"701 72 90 129 108 5 True \n",
"702 70 125 80 111 5 True \n",
"703 80 110 90 121 5 True \n",
"704 70 125 80 111 5 True \n",
"705 70 145 80 101 5 True \n",
"706 100 150 120 90 5 True \n",
"707 120 120 100 90 5 True \n",
"708 90 115 80 101 5 True \n",
"709 90 105 80 91 5 True \n",
"710 90 130 90 95 5 True \n",
"711 100 120 90 95 5 True \n",
"712 90 170 100 95 5 True \n",
"792 95 131 98 99 6 True \n",
"793 95 131 98 99 6 True \n",
"794 121 81 95 95 6 True \n",
"795 150 100 150 50 6 True \n",
"796 110 160 110 110 6 True \n",
"797 60 150 130 70 6 True \n",
"798 60 170 130 80 6 True \n",
"799 120 130 90 70 6 True "
]
},
"execution_count": 96,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"legendary = pokemon[pokemon.legendary]\n",
"legendary"
]
},
{
"cell_type": "markdown",
"id": "767e3751-743e-4849-973b-3ab97d4f37ee",
"metadata": {},
"source": [
"### Filtering by column data\n",
"If you want to filter by content inside a column you will need to utilize a variable to hold the information and use a relational operator \"==\". You can also use others.\n",
"Use: `variable = series[series.column == \"keyword\"]`. Call the variable name to show. Use relational operators to display combinations of filtered data. See the 2nd example for use of relational operators to filter by several keywords in data."
]
},
{
"cell_type": "code",
"execution_count": 97,
"id": "56e03064-c7ee-431e-b4d7-f61fdc8aa7bf",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>name</th>\n",
" <th>type</th>\n",
" <th>subtype</th>\n",
" <th>total</th>\n",
" <th>hp</th>\n",
" <th>attack</th>\n",
" <th>defense</th>\n",
" <th>special_attack</th>\n",
" <th>special_defense</th>\n",
" <th>speed</th>\n",
" <th>generation</th>\n",
" <th>legendary</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>133</th>\n",
" <td>Jynx</td>\n",
" <td>Ice</td>\n",
" <td>Psychic</td>\n",
" <td>455</td>\n",
" <td>65</td>\n",
" <td>50</td>\n",
" <td>35</td>\n",
" <td>115</td>\n",
" <td>95</td>\n",
" <td>95</td>\n",
" <td>1</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156</th>\n",
" <td>Articuno</td>\n",
" <td>Ice</td>\n",
" <td>Flying</td>\n",
" <td>580</td>\n",
" <td>90</td>\n",
" <td>85</td>\n",
" <td>100</td>\n",
" <td>95</td>\n",
" <td>125</td>\n",
" <td>85</td>\n",
" <td>1</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>238</th>\n",
" <td>Swinub</td>\n",
" <td>Ice</td>\n",
" <td>Ground</td>\n",
" <td>250</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>40</td>\n",
" <td>30</td>\n",
" <td>30</td>\n",
" <td>50</td>\n",
" <td>2</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>239</th>\n",
" <td>Piloswine</td>\n",
" <td>Ice</td>\n",
" <td>Ground</td>\n",
" <td>450</td>\n",
" <td>100</td>\n",
" <td>100</td>\n",
" <td>80</td>\n",
" <td>60</td>\n",
" <td>60</td>\n",
" <td>50</td>\n",
" <td>2</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>243</th>\n",
" <td>Delibird</td>\n",
" <td>Ice</td>\n",
" <td>Flying</td>\n",
" <td>330</td>\n",
" <td>45</td>\n",
" <td>55</td>\n",
" <td>45</td>\n",
" <td>65</td>\n",
" <td>45</td>\n",
" <td>75</td>\n",
" <td>2</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>257</th>\n",
" <td>Smoochum</td>\n",
" <td>Ice</td>\n",
" <td>Psychic</td>\n",
" <td>305</td>\n",
" <td>45</td>\n",
" <td>30</td>\n",
" <td>15</td>\n",
" <td>85</td>\n",
" <td>65</td>\n",
" <td>65</td>\n",
" <td>2</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>395</th>\n",
" <td>Snorunt</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>300</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>396</th>\n",
" <td>Glalie</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>480</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>397</th>\n",
" <td>GlalieMega Glalie</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>580</td>\n",
" <td>80</td>\n",
" <td>120</td>\n",
" <td>80</td>\n",
" <td>120</td>\n",
" <td>80</td>\n",
" <td>100</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>398</th>\n",
" <td>Spheal</td>\n",
" <td>Ice</td>\n",
" <td>Water</td>\n",
" <td>290</td>\n",
" <td>70</td>\n",
" <td>40</td>\n",
" <td>50</td>\n",
" <td>55</td>\n",
" <td>50</td>\n",
" <td>25</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>399</th>\n",
" <td>Sealeo</td>\n",
" <td>Ice</td>\n",
" <td>Water</td>\n",
" <td>410</td>\n",
" <td>90</td>\n",
" <td>60</td>\n",
" <td>70</td>\n",
" <td>75</td>\n",
" <td>70</td>\n",
" <td>45</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>400</th>\n",
" <td>Walrein</td>\n",
" <td>Ice</td>\n",
" <td>Water</td>\n",
" <td>530</td>\n",
" <td>110</td>\n",
" <td>80</td>\n",
" <td>90</td>\n",
" <td>95</td>\n",
" <td>90</td>\n",
" <td>65</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>415</th>\n",
" <td>Regice</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>580</td>\n",
" <td>80</td>\n",
" <td>50</td>\n",
" <td>100</td>\n",
" <td>100</td>\n",
" <td>200</td>\n",
" <td>50</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>522</th>\n",
" <td>Glaceon</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>525</td>\n",
" <td>65</td>\n",
" <td>60</td>\n",
" <td>110</td>\n",
" <td>130</td>\n",
" <td>95</td>\n",
" <td>65</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>524</th>\n",
" <td>Mamoswine</td>\n",
" <td>Ice</td>\n",
" <td>Ground</td>\n",
" <td>530</td>\n",
" <td>110</td>\n",
" <td>130</td>\n",
" <td>80</td>\n",
" <td>70</td>\n",
" <td>60</td>\n",
" <td>80</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>530</th>\n",
" <td>Froslass</td>\n",
" <td>Ice</td>\n",
" <td>Ghost</td>\n",
" <td>480</td>\n",
" <td>70</td>\n",
" <td>80</td>\n",
" <td>70</td>\n",
" <td>80</td>\n",
" <td>70</td>\n",
" <td>110</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>643</th>\n",
" <td>Vanillite</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>305</td>\n",
" <td>36</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>65</td>\n",
" <td>60</td>\n",
" <td>44</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>644</th>\n",
" <td>Vanillish</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>395</td>\n",
" <td>51</td>\n",
" <td>65</td>\n",
" <td>65</td>\n",
" <td>80</td>\n",
" <td>75</td>\n",
" <td>59</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>645</th>\n",
" <td>Vanilluxe</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>535</td>\n",
" <td>71</td>\n",
" <td>95</td>\n",
" <td>85</td>\n",
" <td>110</td>\n",
" <td>95</td>\n",
" <td>79</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>674</th>\n",
" <td>Cubchoo</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>305</td>\n",
" <td>55</td>\n",
" <td>70</td>\n",
" <td>40</td>\n",
" <td>60</td>\n",
" <td>40</td>\n",
" <td>40</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>675</th>\n",
" <td>Beartic</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>485</td>\n",
" <td>95</td>\n",
" <td>110</td>\n",
" <td>80</td>\n",
" <td>70</td>\n",
" <td>80</td>\n",
" <td>50</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>676</th>\n",
" <td>Cryogonal</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>485</td>\n",
" <td>70</td>\n",
" <td>50</td>\n",
" <td>30</td>\n",
" <td>95</td>\n",
" <td>135</td>\n",
" <td>105</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>788</th>\n",
" <td>Bergmite</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>304</td>\n",
" <td>55</td>\n",
" <td>69</td>\n",
" <td>85</td>\n",
" <td>32</td>\n",
" <td>35</td>\n",
" <td>28</td>\n",
" <td>6</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>789</th>\n",
" <td>Avalugg</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>514</td>\n",
" <td>95</td>\n",
" <td>117</td>\n",
" <td>184</td>\n",
" <td>44</td>\n",
" <td>46</td>\n",
" <td>28</td>\n",
" <td>6</td>\n",
" <td>False</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" name type subtype total hp attack defense \\\n",
"133 Jynx Ice Psychic 455 65 50 35 \n",
"156 Articuno Ice Flying 580 90 85 100 \n",
"238 Swinub Ice Ground 250 50 50 40 \n",
"239 Piloswine Ice Ground 450 100 100 80 \n",
"243 Delibird Ice Flying 330 45 55 45 \n",
"257 Smoochum Ice Psychic 305 45 30 15 \n",
"395 Snorunt Ice NaN 300 50 50 50 \n",
"396 Glalie Ice NaN 480 80 80 80 \n",
"397 GlalieMega Glalie Ice NaN 580 80 120 80 \n",
"398 Spheal Ice Water 290 70 40 50 \n",
"399 Sealeo Ice Water 410 90 60 70 \n",
"400 Walrein Ice Water 530 110 80 90 \n",
"415 Regice Ice NaN 580 80 50 100 \n",
"522 Glaceon Ice NaN 525 65 60 110 \n",
"524 Mamoswine Ice Ground 530 110 130 80 \n",
"530 Froslass Ice Ghost 480 70 80 70 \n",
"643 Vanillite Ice NaN 305 36 50 50 \n",
"644 Vanillish Ice NaN 395 51 65 65 \n",
"645 Vanilluxe Ice NaN 535 71 95 85 \n",
"674 Cubchoo Ice NaN 305 55 70 40 \n",
"675 Beartic Ice NaN 485 95 110 80 \n",
"676 Cryogonal Ice NaN 485 70 50 30 \n",
"788 Bergmite Ice NaN 304 55 69 85 \n",
"789 Avalugg Ice NaN 514 95 117 184 \n",
"\n",
" special_attack special_defense speed generation legendary \n",
"133 115 95 95 1 False \n",
"156 95 125 85 1 True \n",
"238 30 30 50 2 False \n",
"239 60 60 50 2 False \n",
"243 65 45 75 2 False \n",
"257 85 65 65 2 False \n",
"395 50 50 50 3 False \n",
"396 80 80 80 3 False \n",
"397 120 80 100 3 False \n",
"398 55 50 25 3 False \n",
"399 75 70 45 3 False \n",
"400 95 90 65 3 False \n",
"415 100 200 50 3 True \n",
"522 130 95 65 4 False \n",
"524 70 60 80 4 False \n",
"530 80 70 110 4 False \n",
"643 65 60 44 5 False \n",
"644 80 75 59 5 False \n",
"645 110 95 79 5 False \n",
"674 60 40 40 5 False \n",
"675 70 80 50 5 False \n",
"676 95 135 105 5 False \n",
"788 32 35 28 6 False \n",
"789 44 46 28 6 False "
]
},
"execution_count": 97,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ice_pokemon = pokemon[pokemon.type == \"Ice\"]\n",
"ice_pokemon"
]
},
{
"cell_type": "code",
"execution_count": 98,
"id": "8b2db155-c8da-48be-bf60-ccb98613d35e",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
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" <th></th>\n",
" <th>name</th>\n",
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" <th>4</th>\n",
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" <tr>\n",
" <th>7</th>\n",
" <td>CharizardMega Charizard X</td>\n",
" <td>Fire</td>\n",
" <td>Dragon</td>\n",
" <td>634</td>\n",
" <td>78</td>\n",
" <td>130</td>\n",
" <td>111</td>\n",
" <td>130</td>\n",
" <td>85</td>\n",
" <td>100</td>\n",
" <td>1</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>CharizardMega Charizard Y</td>\n",
" <td>Fire</td>\n",
" <td>Flying</td>\n",
" <td>634</td>\n",
" <td>78</td>\n",
" <td>104</td>\n",
" <td>78</td>\n",
" <td>159</td>\n",
" <td>115</td>\n",
" <td>100</td>\n",
" <td>1</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>42</th>\n",
" <td>Vulpix</td>\n",
" <td>Fire</td>\n",
" <td>NaN</td>\n",
" <td>299</td>\n",
" <td>38</td>\n",
" <td>41</td>\n",
" <td>40</td>\n",
" <td>50</td>\n",
" <td>65</td>\n",
" <td>65</td>\n",
" <td>1</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>43</th>\n",
" <td>Ninetales</td>\n",
" <td>Fire</td>\n",
" <td>NaN</td>\n",
" <td>505</td>\n",
" <td>73</td>\n",
" <td>76</td>\n",
" <td>75</td>\n",
" <td>81</td>\n",
" <td>100</td>\n",
" <td>100</td>\n",
" <td>1</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>63</th>\n",
" <td>Growlithe</td>\n",
" <td>Fire</td>\n",
" <td>NaN</td>\n",
" <td>350</td>\n",
" <td>55</td>\n",
" <td>70</td>\n",
" <td>45</td>\n",
" <td>70</td>\n",
" <td>50</td>\n",
" <td>60</td>\n",
" <td>1</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>64</th>\n",
" <td>Arcanine</td>\n",
" <td>Fire</td>\n",
" <td>NaN</td>\n",
" <td>555</td>\n",
" <td>90</td>\n",
" <td>110</td>\n",
" <td>80</td>\n",
" <td>100</td>\n",
" <td>80</td>\n",
" <td>95</td>\n",
" <td>1</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>83</th>\n",
" <td>Ponyta</td>\n",
" <td>Fire</td>\n",
" <td>NaN</td>\n",
" <td>410</td>\n",
" <td>50</td>\n",
" <td>85</td>\n",
" <td>55</td>\n",
" <td>65</td>\n",
" <td>65</td>\n",
" <td>90</td>\n",
" <td>1</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>84</th>\n",
" <td>Rapidash</td>\n",
" <td>Fire</td>\n",
" <td>NaN</td>\n",
" <td>500</td>\n",
" <td>65</td>\n",
" <td>100</td>\n",
" <td>70</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
" <td>105</td>\n",
" <td>1</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>135</th>\n",
" <td>Magmar</td>\n",
" <td>Fire</td>\n",
" <td>NaN</td>\n",
" <td>495</td>\n",
" <td>65</td>\n",
" <td>95</td>\n",
" <td>57</td>\n",
" <td>100</td>\n",
" <td>85</td>\n",
" <td>93</td>\n",
" <td>1</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147</th>\n",
" <td>Flareon</td>\n",
" <td>Fire</td>\n",
" <td>NaN</td>\n",
" <td>525</td>\n",
" <td>65</td>\n",
" <td>130</td>\n",
" <td>60</td>\n",
" <td>95</td>\n",
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" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>158</th>\n",
" <td>Moltres</td>\n",
" <td>Fire</td>\n",
" <td>Flying</td>\n",
" <td>580</td>\n",
" <td>90</td>\n",
" <td>100</td>\n",
" <td>90</td>\n",
" <td>125</td>\n",
" <td>85</td>\n",
" <td>90</td>\n",
" <td>1</td>\n",
" <td>True</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" name type subtype total hp attack defense \\\n",
"4 Charmander Fire NaN 309 39 52 43 \n",
"5 Charmeleon Fire NaN 405 58 64 58 \n",
"6 Charizard Fire Flying 534 78 84 78 \n",
"7 CharizardMega Charizard X Fire Dragon 634 78 130 111 \n",
"8 CharizardMega Charizard Y Fire Flying 634 78 104 78 \n",
"42 Vulpix Fire NaN 299 38 41 40 \n",
"43 Ninetales Fire NaN 505 73 76 75 \n",
"63 Growlithe Fire NaN 350 55 70 45 \n",
"64 Arcanine Fire NaN 555 90 110 80 \n",
"83 Ponyta Fire NaN 410 50 85 55 \n",
"84 Rapidash Fire NaN 500 65 100 70 \n",
"135 Magmar Fire NaN 495 65 95 57 \n",
"147 Flareon Fire NaN 525 65 130 60 \n",
"158 Moltres Fire Flying 580 90 100 90 \n",
"\n",
" special_attack special_defense speed generation legendary \n",
"4 60 50 65 1 False \n",
"5 80 65 80 1 False \n",
"6 109 85 100 1 False \n",
"7 130 85 100 1 False \n",
"8 159 115 100 1 False \n",
"42 50 65 65 1 False \n",
"43 81 100 100 1 False \n",
"63 70 50 60 1 False \n",
"64 100 80 95 1 False \n",
"83 65 65 90 1 False \n",
"84 80 80 105 1 False \n",
"135 100 85 93 1 False \n",
"147 95 110 65 1 False \n",
"158 125 85 90 1 True "
]
},
"execution_count": 98,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Displays only gen1 fire pokemon\n",
"fire_gen1 = pokemon[(pokemon.generation == 1) & (pokemon.type == \"Fire\")] \n",
"fire_gen1"
]
},
{
"cell_type": "code",
"execution_count": 99,
"id": "c8453566-a710-4976-a205-aec5328da430",
"metadata": {},
"outputs": [
{
"data": {
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"\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>name</th>\n",
" <th>type</th>\n",
" <th>subtype</th>\n",
" <th>total</th>\n",
" <th>hp</th>\n",
" <th>attack</th>\n",
" <th>defense</th>\n",
" <th>special_attack</th>\n",
" <th>special_defense</th>\n",
" <th>speed</th>\n",
" <th>generation</th>\n",
" <th>legendary</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Venusaur</td>\n",
" <td>Grass</td>\n",
" <td>Poison</td>\n",
" <td>525</td>\n",
" <td>80</td>\n",
" <td>82</td>\n",
" <td>83</td>\n",
" <td>100</td>\n",
" <td>100</td>\n",
" <td>80</td>\n",
" <td>1</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Charmeleon</td>\n",
" <td>Fire</td>\n",
" <td>NaN</td>\n",
" <td>405</td>\n",
" <td>58</td>\n",
" <td>64</td>\n",
" <td>58</td>\n",
" <td>80</td>\n",
" <td>65</td>\n",
" <td>80</td>\n",
" <td>1</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>Charizard</td>\n",
" <td>Fire</td>\n",
" <td>Flying</td>\n",
" <td>534</td>\n",
" <td>78</td>\n",
" <td>84</td>\n",
" <td>78</td>\n",
" <td>109</td>\n",
" <td>85</td>\n",
" <td>100</td>\n",
" <td>1</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>CharizardMega Charizard Y</td>\n",
" <td>Fire</td>\n",
" <td>Flying</td>\n",
" <td>634</td>\n",
" <td>78</td>\n",
" <td>104</td>\n",
" <td>78</td>\n",
" <td>159</td>\n",
" <td>115</td>\n",
" <td>100</td>\n",
" <td>1</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>PidgeotMega Pidgeot</td>\n",
" <td>Normal</td>\n",
" <td>Flying</td>\n",
" <td>579</td>\n",
" <td>83</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
" <td>135</td>\n",
" <td>80</td>\n",
" <td>121</td>\n",
" <td>1</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>771</th>\n",
" <td>Hawlucha</td>\n",
" <td>Fighting</td>\n",
" <td>Flying</td>\n",
" <td>500</td>\n",
" <td>78</td>\n",
" <td>92</td>\n",
" <td>75</td>\n",
" <td>74</td>\n",
" <td>63</td>\n",
" <td>118</td>\n",
" <td>6</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>772</th>\n",
" <td>Dedenne</td>\n",
" <td>Electric</td>\n",
" <td>Fairy</td>\n",
" <td>431</td>\n",
" <td>67</td>\n",
" <td>58</td>\n",
" <td>57</td>\n",
" <td>81</td>\n",
" <td>67</td>\n",
" <td>101</td>\n",
" <td>6</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>776</th>\n",
" <td>Goodra</td>\n",
" <td>Dragon</td>\n",
" <td>NaN</td>\n",
" <td>600</td>\n",
" <td>90</td>\n",
" <td>100</td>\n",
" <td>70</td>\n",
" <td>110</td>\n",
" <td>150</td>\n",
" <td>80</td>\n",
" <td>6</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>791</th>\n",
" <td>Noivern</td>\n",
" <td>Flying</td>\n",
" <td>Dragon</td>\n",
" <td>535</td>\n",
" <td>85</td>\n",
" <td>70</td>\n",
" <td>80</td>\n",
" <td>97</td>\n",
" <td>80</td>\n",
" <td>123</td>\n",
" <td>6</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>798</th>\n",
" <td>HoopaHoopa Unbound</td>\n",
" <td>Psychic</td>\n",
" <td>Dark</td>\n",
" <td>680</td>\n",
" <td>80</td>\n",
" <td>160</td>\n",
" <td>60</td>\n",
" <td>170</td>\n",
" <td>130</td>\n",
" <td>80</td>\n",
" <td>6</td>\n",
" <td>True</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>138 rows × 12 columns</p>\n",
"</div>"
],
"text/plain": [
" name type subtype total hp attack defense \\\n",
"2 Venusaur Grass Poison 525 80 82 83 \n",
"5 Charmeleon Fire NaN 405 58 64 58 \n",
"6 Charizard Fire Flying 534 78 84 78 \n",
"8 CharizardMega Charizard Y Fire Flying 634 78 104 78 \n",
"23 PidgeotMega Pidgeot Normal Flying 579 83 80 80 \n",
".. ... ... ... ... .. ... ... \n",
"771 Hawlucha Fighting Flying 500 78 92 75 \n",
"772 Dedenne Electric Fairy 431 67 58 57 \n",
"776 Goodra Dragon NaN 600 90 100 70 \n",
"791 Noivern Flying Dragon 535 85 70 80 \n",
"798 HoopaHoopa Unbound Psychic Dark 680 80 160 60 \n",
"\n",
" special_attack special_defense speed generation legendary \n",
"2 100 100 80 1 False \n",
"5 80 65 80 1 False \n",
"6 109 85 100 1 False \n",
"8 159 115 100 1 False \n",
"23 135 80 121 1 False \n",
".. ... ... ... ... ... \n",
"771 74 63 118 6 False \n",
"772 81 67 101 6 False \n",
"776 110 150 80 6 False \n",
"791 97 80 123 6 False \n",
"798 170 130 80 6 True \n",
"\n",
"[138 rows x 12 columns]"
]
},
"execution_count": 99,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Displays pokemon with a special attack greater than 70 and a speed greater than a 70 and a defense less than 90.\n",
"spAttack_speed_defense = pokemon[(pokemon.special_attack > 70) & (pokemon.speed > 70) & (pokemon.defense < 90)]\n",
"spAttack_speed_defense"
]
},
{
"cell_type": "markdown",
"id": "fe22b538-d04d-4fdb-a8fc-9dd36dab1ab1",
"metadata": {},
"source": [
"___\n",
"### Grouping\n",
"Grouping allows you to group data frames together for powerful comparison abilities."
]
},
{
"cell_type": "markdown",
"id": "d3ae0387-ece3-4060-848d-68045f53b0be",
"metadata": {},
"source": [
"### groupby()\n",
"Allows you to group columns together. Use: `series.groupby(\"column\").[other methods]`\n",
"\n",
"1. In the first example below we are taking the mean speeds and grouping them by the type of pokemon. The mean speed of Bug pokemon is 61.6.\n",
"\n",
"2. In the second example we are grouping and sorting by amount the mean amount of legendary pokemon in each generation. Generation 3 has the most legendary pokemon. Note that this can of course be saved in a variable.\n",
"\n",
"3. In the third example we are grouping by the type again, but then we are finding the mean values of several columns and sorting the values by the amount of HP. Notice we need mean() for any values to be displayed.\n",
"\n",
"4. In the final example we are grouping by generation, then seeing attack, special attack and defense. We are grouping by defense."
]
},
{
"cell_type": "code",
"execution_count": 100,
"id": "a59dbfd8-3f7c-4677-8d1b-73fefc98ea5b",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"type\n",
"Bug 61.681159\n",
"Dark 76.161290\n",
"Dragon 83.031250\n",
"Electric 84.500000\n",
"Fairy 48.588235\n",
"Fighting 66.074074\n",
"Fire 74.442308\n",
"Flying 102.500000\n",
"Ghost 64.343750\n",
"Grass 61.928571\n",
"Ground 63.906250\n",
"Ice 63.458333\n",
"Normal 71.551020\n",
"Poison 63.571429\n",
"Psychic 81.491228\n",
"Rock 55.909091\n",
"Steel 55.259259\n",
"Water 65.964286\n",
"Name: speed, dtype: float64"
]
},
"execution_count": 100,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pokemon.groupby(\"type\").speed.mean()"
]
},
{
"cell_type": "code",
"execution_count": 101,
"id": "d8d6580b-8b82-47c2-aab9-b28b5c07734b",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"generation\n",
"1 3.614458\n",
"2 4.716981\n",
"5 9.090909\n",
"6 9.756098\n",
"4 10.743802\n",
"3 11.250000\n",
"Name: legendary, dtype: float64"
]
},
"execution_count": 101,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"legendary_count_generation = pokemon.groupby(\"generation\").legendary.mean().sort_values() * 100\n",
"legendary_count_generation "
]
},
{
"cell_type": "code",
"execution_count": 102,
"id": "a4c40e66-7a3b-4209-94f5-89e4f0d758e2",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
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" text-align: right;\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>hp</th>\n",
" <th>attack</th>\n",
" <th>defense</th>\n",
" </tr>\n",
" <tr>\n",
" <th>type</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Bug</th>\n",
" <td>56.884058</td>\n",
" <td>70.971014</td>\n",
" <td>70.724638</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Electric</th>\n",
" <td>59.795455</td>\n",
" <td>69.090909</td>\n",
" <td>66.295455</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ghost</th>\n",
" <td>64.437500</td>\n",
" <td>73.781250</td>\n",
" <td>81.187500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Steel</th>\n",
" <td>65.222222</td>\n",
" <td>92.703704</td>\n",
" <td>126.370370</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Rock</th>\n",
" <td>65.363636</td>\n",
" <td>92.863636</td>\n",
" <td>100.795455</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dark</th>\n",
" <td>66.806452</td>\n",
" <td>88.387097</td>\n",
" <td>70.225806</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Poison</th>\n",
" <td>67.250000</td>\n",
" <td>74.678571</td>\n",
" <td>68.821429</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Grass</th>\n",
" <td>67.271429</td>\n",
" <td>73.214286</td>\n",
" <td>70.800000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fighting</th>\n",
" <td>69.851852</td>\n",
" <td>96.777778</td>\n",
" <td>65.925926</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fire</th>\n",
" <td>69.903846</td>\n",
" <td>84.769231</td>\n",
" <td>67.769231</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Psychic</th>\n",
" <td>70.631579</td>\n",
" <td>71.456140</td>\n",
" <td>67.684211</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Flying</th>\n",
" <td>70.750000</td>\n",
" <td>78.750000</td>\n",
" <td>66.250000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ice</th>\n",
" <td>72.000000</td>\n",
" <td>72.750000</td>\n",
" <td>71.416667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Water</th>\n",
" <td>72.062500</td>\n",
" <td>74.151786</td>\n",
" <td>72.946429</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ground</th>\n",
" <td>73.781250</td>\n",
" <td>95.750000</td>\n",
" <td>84.843750</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fairy</th>\n",
" <td>74.117647</td>\n",
" <td>61.529412</td>\n",
" <td>65.705882</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Normal</th>\n",
" <td>77.275510</td>\n",
" <td>73.469388</td>\n",
" <td>59.846939</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dragon</th>\n",
" <td>83.312500</td>\n",
" <td>112.125000</td>\n",
" <td>86.375000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" hp attack defense\n",
"type \n",
"Bug 56.884058 70.971014 70.724638\n",
"Electric 59.795455 69.090909 66.295455\n",
"Ghost 64.437500 73.781250 81.187500\n",
"Steel 65.222222 92.703704 126.370370\n",
"Rock 65.363636 92.863636 100.795455\n",
"Dark 66.806452 88.387097 70.225806\n",
"Poison 67.250000 74.678571 68.821429\n",
"Grass 67.271429 73.214286 70.800000\n",
"Fighting 69.851852 96.777778 65.925926\n",
"Fire 69.903846 84.769231 67.769231\n",
"Psychic 70.631579 71.456140 67.684211\n",
"Flying 70.750000 78.750000 66.250000\n",
"Ice 72.000000 72.750000 71.416667\n",
"Water 72.062500 74.151786 72.946429\n",
"Ground 73.781250 95.750000 84.843750\n",
"Fairy 74.117647 61.529412 65.705882\n",
"Normal 77.275510 73.469388 59.846939\n",
"Dragon 83.312500 112.125000 86.375000"
]
},
"execution_count": 102,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ptypes = pokemon.groupby(\"type\")[[\"hp\", \"attack\", \"defense\"]].mean().sort_values(\"hp\")\n",
"ptypes"
]
},
{
"cell_type": "code",
"execution_count": 103,
"id": "5cb709b9-0d69-4692-bf85-72e5c11f861c",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
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" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>attack</th>\n",
" <th>special_attack</th>\n",
" <th>defense</th>\n",
" </tr>\n",
" <tr>\n",
" <th>generation</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>76.638554</td>\n",
" <td>71.819277</td>\n",
" <td>70.861446</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>82.066667</td>\n",
" <td>71.987879</td>\n",
" <td>72.327273</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>72.028302</td>\n",
" <td>65.943396</td>\n",
" <td>73.386792</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>81.625000</td>\n",
" <td>75.806250</td>\n",
" <td>74.100000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>75.804878</td>\n",
" <td>74.292683</td>\n",
" <td>76.682927</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>82.867769</td>\n",
" <td>76.404959</td>\n",
" <td>78.132231</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" attack special_attack defense\n",
"generation \n",
"1 76.638554 71.819277 70.861446\n",
"5 82.066667 71.987879 72.327273\n",
"2 72.028302 65.943396 73.386792\n",
"3 81.625000 75.806250 74.100000\n",
"6 75.804878 74.292683 76.682927\n",
"4 82.867769 76.404959 78.132231"
]
},
"execution_count": 103,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gen_attackpower_defense = pokemon.groupby(\"generation\")[[\"attack\", \"special_attack\", \"defense\"]].mean().sort_values(\"defense\")\n",
"gen_attackpower_defense"
]
},
{
"cell_type": "markdown",
"id": "b71695b7-3fc2-477d-9e53-ea6f3b14187d",
"metadata": {},
"source": [
"___\n",
"### More Complex Grouping (Grouping Multiple objects together)\n",
"Grouping allows you to group data together with multiple columns as well. \n",
"1. This is showing how you would see the mean of legenday type pokemon, broken down by each type and subtype. We grouped type and subtype to get all the possible combinations, sorted by legendary mean. We also are display values that are greater than 0.\n",
" \n",
"2. The second example is grouping by generation and type, displaying hp, attack and defense. Its being sorted by attack power.\n",
" \n",
"3. In the third example we are doing the same thing as 2, however we are using `sort_values(by=[\"generation\", \"attack\", \"defense\"]` to sort first by generation, then sort the individual values within attack / defense."
]
},
{
"cell_type": "code",
"execution_count": 104,
"id": "25fc487c-a748-480e-9c91-b1a03f5c2abf",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"type subtype \n",
"Steel Psychic 0.142857\n",
"Psychic Flying 0.166667\n",
"Grass Flying 0.200000\n",
"Dragon Ground 0.200000\n",
"Dark Flying 0.200000\n",
"Grass Fighting 0.333333\n",
"Dragon Flying 0.333333\n",
"Fire Flying 0.333333\n",
"Psychic Fighting 0.333333\n",
"Ground Flying 0.500000\n",
"Ice Flying 0.500000\n",
"Water Dragon 0.500000\n",
"Electric Flying 0.600000\n",
"Rock Fairy 0.666667\n",
"Psychic Ghost 1.000000\n",
"Ground Fire 1.000000\n",
"Ghost Dragon 1.000000\n",
"Fire Water 1.000000\n",
" Steel 1.000000\n",
"Psychic Dark 1.000000\n",
" Fire 1.000000\n",
"Steel Dragon 1.000000\n",
"Rock Fighting 1.000000\n",
"Dragon Psychic 1.000000\n",
" Ice 1.000000\n",
" Fire 1.000000\n",
"Steel Fighting 1.000000\n",
"Dragon Electric 1.000000\n",
"Name: legendary, dtype: float64"
]
},
"execution_count": 104,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"legendary_percentages = pokemon.groupby([\"type\", \"subtype\"]).legendary.mean().sort_values() \n",
"legendary_percentages[legendary_percentages > 0]"
]
},
{
"cell_type": "code",
"execution_count": 105,
"id": "450ba5e2-17f5-4ee6-9d3a-54cb41daaaff",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
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" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th></th>\n",
" <th>attack</th>\n",
" <th>defense</th>\n",
" </tr>\n",
" <tr>\n",
" <th>type</th>\n",
" <th>generation</th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Bug</th>\n",
" <th>1</th>\n",
" <td>76.428571</td>\n",
" <td>60.357143</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dragon</th>\n",
" <th>1</th>\n",
" <td>94.000000</td>\n",
" <td>68.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Electric</th>\n",
" <th>1</th>\n",
" <td>62.000000</td>\n",
" <td>64.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fairy</th>\n",
" <th>1</th>\n",
" <td>57.500000</td>\n",
" <td>60.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Psychic</th>\n",
" <th>1</th>\n",
" <td>79.181818</td>\n",
" <td>63.181818</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fire</th>\n",
" <th>1</th>\n",
" <td>88.642857</td>\n",
" <td>67.142857</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Poison</th>\n",
" <th>1</th>\n",
" <td>74.428571</td>\n",
" <td>67.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Rock</th>\n",
" <th>1</th>\n",
" <td>87.500000</td>\n",
" <td>107.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fighting</th>\n",
" <th>1</th>\n",
" <td>102.857143</td>\n",
" <td>61.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ghost</th>\n",
" <th>1</th>\n",
" <td>53.750000</td>\n",
" <td>53.750000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Normal</th>\n",
" <th>1</th>\n",
" <td>70.625000</td>\n",
" <td>56.583333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ground</th>\n",
" <th>1</th>\n",
" <td>81.875000</td>\n",
" <td>86.250000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Water</th>\n",
" <th>1</th>\n",
" <td>74.193548</td>\n",
" <td>83.193548</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Grass</th>\n",
" <th>1</th>\n",
" <td>72.923077</td>\n",
" <td>73.692308</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ice</th>\n",
" <th>1</th>\n",
" <td>67.500000</td>\n",
" <td>67.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Steel</th>\n",
" <th>2</th>\n",
" <td>96.666667</td>\n",
" <td>190.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Normal</th>\n",
" <th>2</th>\n",
" <td>63.133333</td>\n",
" <td>54.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fire</th>\n",
" <th>2</th>\n",
" <td>76.250000</td>\n",
" <td>68.875000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ice</th>\n",
" <th>2</th>\n",
" <td>58.750000</td>\n",
" <td>45.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Poison</th>\n",
" <th>2</th>\n",
" <td>90.000000</td>\n",
" <td>80.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fighting</th>\n",
" <th>2</th>\n",
" <td>65.000000</td>\n",
" <td>65.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fairy</th>\n",
" <th>2</th>\n",
" <td>57.000000</td>\n",
" <td>60.600000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Rock</th>\n",
" <th>2</th>\n",
" <td>109.200000</td>\n",
" <td>99.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Water</th>\n",
" <th>2</th>\n",
" <td>68.111111</td>\n",
" <td>72.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ghost</th>\n",
" <th>2</th>\n",
" <td>60.000000</td>\n",
" <td>60.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dark</th>\n",
" <th>2</th>\n",
" <td>80.833333</td>\n",
" <td>62.833333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ground</th>\n",
" <th>2</th>\n",
" <td>85.000000</td>\n",
" <td>95.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Grass</th>\n",
" <th>2</th>\n",
" <td>57.000000</td>\n",
" <td>65.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Psychic</th>\n",
" <th>2</th>\n",
" <td>69.285714</td>\n",
" <td>73.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Electric</th>\n",
" <th>2</th>\n",
" <td>64.714286</td>\n",
" <td>58.857143</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Bug</th>\n",
" <th>2</th>\n",
" <td>85.416667</td>\n",
" <td>93.750000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dragon</th>\n",
" <th>3</th>\n",
" <td>113.333333</td>\n",
" <td>95.833333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fire</th>\n",
" <th>3</th>\n",
" <td>98.750000</td>\n",
" <td>75.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Normal</th>\n",
" <th>3</th>\n",
" <td>69.888889</td>\n",
" <td>57.277778</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ice</th>\n",
" <th>3</th>\n",
" <td>68.571429</td>\n",
" <td>74.285714</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fighting</th>\n",
" <th>3</th>\n",
" <td>76.000000</td>\n",
" <td>61.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Poison</th>\n",
" <th>3</th>\n",
" <td>72.000000</td>\n",
" <td>65.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Steel</th>\n",
" <th>3</th>\n",
" <td>98.750000</td>\n",
" <td>130.833333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Electric</th>\n",
" <th>3</th>\n",
" <td>57.000000</td>\n",
" <td>54.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Psychic</th>\n",
" <th>3</th>\n",
" <td>70.666667</td>\n",
" <td>60.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Rock</th>\n",
" <th>3</th>\n",
" <td>79.625000</td>\n",
" <td>101.125000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ground</th>\n",
" <th>3</th>\n",
" <td>101.428571</td>\n",
" <td>90.714286</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ghost</th>\n",
" <th>3</th>\n",
" <td>93.000000</td>\n",
" <td>79.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Grass</th>\n",
" <th>3</th>\n",
" <td>77.923077</td>\n",
" <td>56.769231</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dark</th>\n",
" <th>3</th>\n",
" <td>97.500000</td>\n",
" <td>70.833333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Bug</th>\n",
" <th>3</th>\n",
" <td>55.833333</td>\n",
" <td>54.083333</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">Water</th>\n",
" <th>3</th>\n",
" <td>80.666667</td>\n",
" <td>67.962963</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>72.461538</td>\n",
" <td>67.461538</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Bug</th>\n",
" <th>4</th>\n",
" <td>62.600000</td>\n",
" <td>70.200000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ghost</th>\n",
" <th>4</th>\n",
" <td>86.000000</td>\n",
" <td>85.857143</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dark</th>\n",
" <th>4</th>\n",
" <td>111.666667</td>\n",
" <td>69.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Grass</th>\n",
" <th>4</th>\n",
" <td>84.000000</td>\n",
" <td>80.066667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ice</th>\n",
" <th>4</th>\n",
" <td>90.000000</td>\n",
" <td>86.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fire</th>\n",
" <th>4</th>\n",
" <td>85.000000</td>\n",
" <td>68.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ground</th>\n",
" <th>4</th>\n",
" <td>104.750000</td>\n",
" <td>112.750000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fighting</th>\n",
" <th>4</th>\n",
" <td>108.333333</td>\n",
" <td>66.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Normal</th>\n",
" <th>4</th>\n",
" <td>83.055556</td>\n",
" <td>62.722222</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Steel</th>\n",
" <th>4</th>\n",
" <td>77.666667</td>\n",
" <td>107.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Rock</th>\n",
" <th>4</th>\n",
" <td>86.500000</td>\n",
" <td>104.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fairy</th>\n",
" <th>4</th>\n",
" <td>50.000000</td>\n",
" <td>95.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Electric</th>\n",
" <th>4</th>\n",
" <td>73.583333</td>\n",
" <td>85.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Psychic</th>\n",
" <th>4</th>\n",
" <td>90.000000</td>\n",
" <td>85.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Poison</th>\n",
" <th>4</th>\n",
" <td>77.166667</td>\n",
" <td>69.833333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dragon</th>\n",
" <th>4</th>\n",
" <td>115.000000</td>\n",
" <td>80.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Normal</th>\n",
" <th>5</th>\n",
" <td>83.315789</td>\n",
" <td>69.421053</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fighting</th>\n",
" <th>5</th>\n",
" <td>108.571429</td>\n",
" <td>72.142857</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ground</th>\n",
" <th>5</th>\n",
" <td>102.500000</td>\n",
" <td>65.400000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fire</th>\n",
" <th>5</th>\n",
" <td>87.444444</td>\n",
" <td>60.777778</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Flying</th>\n",
" <th>5</th>\n",
" <td>107.500000</td>\n",
" <td>75.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Rock</th>\n",
" <th>5</th>\n",
" <td>116.000000</td>\n",
" <td>86.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Psychic</th>\n",
" <th>5</th>\n",
" <td>52.500000</td>\n",
" <td>65.571429</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Electric</th>\n",
" <th>5</th>\n",
" <td>88.750000</td>\n",
" <td>60.625000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ice</th>\n",
" <th>5</th>\n",
" <td>73.333333</td>\n",
" <td>58.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dark</th>\n",
" <th>5</th>\n",
" <td>81.384615</td>\n",
" <td>71.692308</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Grass</th>\n",
" <th>5</th>\n",
" <td>65.333333</td>\n",
" <td>72.133333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ghost</th>\n",
" <th>5</th>\n",
" <td>41.000000</td>\n",
" <td>87.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Bug</th>\n",
" <th>5</th>\n",
" <td>77.611111</td>\n",
" <td>78.277778</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Water</th>\n",
" <th>5</th>\n",
" <td>73.277778</td>\n",
" <td>70.277778</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Steel</th>\n",
" <th>5</th>\n",
" <td>81.250000</td>\n",
" <td>102.250000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dragon</th>\n",
" <th>5</th>\n",
" <td>129.000000</td>\n",
" <td>90.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Poison</th>\n",
" <th>5</th>\n",
" <td>72.500000</td>\n",
" <td>72.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Normal</th>\n",
" <th>6</th>\n",
" <td>55.500000</td>\n",
" <td>54.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fighting</th>\n",
" <th>6</th>\n",
" <td>99.333333</td>\n",
" <td>71.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fire</th>\n",
" <th>6</th>\n",
" <td>69.375000</td>\n",
" <td>68.250000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Water</th>\n",
" <th>6</th>\n",
" <td>68.000000</td>\n",
" <td>61.800000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ghost</th>\n",
" <th>6</th>\n",
" <td>81.400000</td>\n",
" <td>89.200000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Grass</th>\n",
" <th>6</th>\n",
" <td>82.200000</td>\n",
" <td>78.400000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Bug</th>\n",
" <th>6</th>\n",
" <td>36.333333</td>\n",
" <td>50.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Steel</th>\n",
" <th>6</th>\n",
" <td>94.000000</td>\n",
" <td>108.200000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ice</th>\n",
" <th>6</th>\n",
" <td>93.000000</td>\n",
" <td>134.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Flying</th>\n",
" <th>6</th>\n",
" <td>50.000000</td>\n",
" <td>57.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fairy</th>\n",
" <th>6</th>\n",
" <td>66.222222</td>\n",
" <td>66.444444</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Electric</th>\n",
" <th>6</th>\n",
" <td>50.333333</td>\n",
" <td>47.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Psychic</th>\n",
" <th>6</th>\n",
" <td>82.800000</td>\n",
" <td>65.200000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Poison</th>\n",
" <th>6</th>\n",
" <td>67.500000</td>\n",
" <td>75.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dark</th>\n",
" <th>6</th>\n",
" <td>92.333333</td>\n",
" <td>78.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Rock</th>\n",
" <th>6</th>\n",
" <td>90.333333</td>\n",
" <td>101.111111</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dragon</th>\n",
" <th>6</th>\n",
" <td>81.250000</td>\n",
" <td>69.750000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" attack defense\n",
"type generation \n",
"Bug 1 76.428571 60.357143\n",
"Dragon 1 94.000000 68.333333\n",
"Electric 1 62.000000 64.666667\n",
"Fairy 1 57.500000 60.500000\n",
"Psychic 1 79.181818 63.181818\n",
"Fire 1 88.642857 67.142857\n",
"Poison 1 74.428571 67.000000\n",
"Rock 1 87.500000 107.500000\n",
"Fighting 1 102.857143 61.000000\n",
"Ghost 1 53.750000 53.750000\n",
"Normal 1 70.625000 56.583333\n",
"Ground 1 81.875000 86.250000\n",
"Water 1 74.193548 83.193548\n",
"Grass 1 72.923077 73.692308\n",
"Ice 1 67.500000 67.500000\n",
"Steel 2 96.666667 190.000000\n",
"Normal 2 63.133333 54.000000\n",
"Fire 2 76.250000 68.875000\n",
"Ice 2 58.750000 45.000000\n",
"Poison 2 90.000000 80.000000\n",
"Fighting 2 65.000000 65.000000\n",
"Fairy 2 57.000000 60.600000\n",
"Rock 2 109.200000 99.000000\n",
"Water 2 68.111111 72.500000\n",
"Ghost 2 60.000000 60.000000\n",
"Dark 2 80.833333 62.833333\n",
"Ground 2 85.000000 95.000000\n",
"Grass 2 57.000000 65.000000\n",
"Psychic 2 69.285714 73.000000\n",
"Electric 2 64.714286 58.857143\n",
"Bug 2 85.416667 93.750000\n",
"Dragon 3 113.333333 95.833333\n",
"Fire 3 98.750000 75.000000\n",
"Normal 3 69.888889 57.277778\n",
"Ice 3 68.571429 74.285714\n",
"Fighting 3 76.000000 61.000000\n",
"Poison 3 72.000000 65.333333\n",
"Steel 3 98.750000 130.833333\n",
"Electric 3 57.000000 54.000000\n",
"Psychic 3 70.666667 60.666667\n",
"Rock 3 79.625000 101.125000\n",
"Ground 3 101.428571 90.714286\n",
"Ghost 3 93.000000 79.000000\n",
"Grass 3 77.923077 56.769231\n",
"Dark 3 97.500000 70.833333\n",
"Bug 3 55.833333 54.083333\n",
"Water 3 80.666667 67.962963\n",
" 4 72.461538 67.461538\n",
"Bug 4 62.600000 70.200000\n",
"Ghost 4 86.000000 85.857143\n",
"Dark 4 111.666667 69.000000\n",
"Grass 4 84.000000 80.066667\n",
"Ice 4 90.000000 86.666667\n",
"Fire 4 85.000000 68.000000\n",
"Ground 4 104.750000 112.750000\n",
"Fighting 4 108.333333 66.000000\n",
"Normal 4 83.055556 62.722222\n",
"Steel 4 77.666667 107.333333\n",
"Rock 4 86.500000 104.333333\n",
"Fairy 4 50.000000 95.000000\n",
"Electric 4 73.583333 85.500000\n",
"Psychic 4 90.000000 85.000000\n",
"Poison 4 77.166667 69.833333\n",
"Dragon 4 115.000000 80.000000\n",
"Normal 5 83.315789 69.421053\n",
"Fighting 5 108.571429 72.142857\n",
"Ground 5 102.500000 65.400000\n",
"Fire 5 87.444444 60.777778\n",
"Flying 5 107.500000 75.000000\n",
"Rock 5 116.000000 86.666667\n",
"Psychic 5 52.500000 65.571429\n",
"Electric 5 88.750000 60.625000\n",
"Ice 5 73.333333 58.333333\n",
"Dark 5 81.384615 71.692308\n",
"Grass 5 65.333333 72.133333\n",
"Ghost 5 41.000000 87.000000\n",
"Bug 5 77.611111 78.277778\n",
"Water 5 73.277778 70.277778\n",
"Steel 5 81.250000 102.250000\n",
"Dragon 5 129.000000 90.000000\n",
"Poison 5 72.500000 72.000000\n",
"Normal 6 55.500000 54.500000\n",
"Fighting 6 99.333333 71.666667\n",
"Fire 6 69.375000 68.250000\n",
"Water 6 68.000000 61.800000\n",
"Ghost 6 81.400000 89.200000\n",
"Grass 6 82.200000 78.400000\n",
"Bug 6 36.333333 50.000000\n",
"Steel 6 94.000000 108.200000\n",
"Ice 6 93.000000 134.500000\n",
"Flying 6 50.000000 57.500000\n",
"Fairy 6 66.222222 66.444444\n",
"Electric 6 50.333333 47.333333\n",
"Psychic 6 82.800000 65.200000\n",
"Poison 6 67.500000 75.000000\n",
"Dark 6 92.333333 78.666667\n",
"Rock 6 90.333333 101.111111\n",
"Dragon 6 81.250000 69.750000"
]
},
"execution_count": 105,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"attack_defense_power_over_gens = pokemon.groupby([\"type\", \"generation\"])[[\"attack\", \"defense\"]].mean().sort_values(\"generation\")\n",
"attack_defense_power_over_gens"
]
},
{
"cell_type": "code",
"execution_count": 106,
"id": "c0d71b51-f301-48d0-80da-130148d4d2ef",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th></th>\n",
" <th>attack</th>\n",
" <th>defense</th>\n",
" </tr>\n",
" <tr>\n",
" <th>type</th>\n",
" <th>generation</th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Ghost</th>\n",
" <th>1</th>\n",
" <td>53.750000</td>\n",
" <td>53.750000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fairy</th>\n",
" <th>1</th>\n",
" <td>57.500000</td>\n",
" <td>60.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Electric</th>\n",
" <th>1</th>\n",
" <td>62.000000</td>\n",
" <td>64.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ice</th>\n",
" <th>1</th>\n",
" <td>67.500000</td>\n",
" <td>67.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Normal</th>\n",
" <th>1</th>\n",
" <td>70.625000</td>\n",
" <td>56.583333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Grass</th>\n",
" <th>1</th>\n",
" <td>72.923077</td>\n",
" <td>73.692308</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Water</th>\n",
" <th>1</th>\n",
" <td>74.193548</td>\n",
" <td>83.193548</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Poison</th>\n",
" <th>1</th>\n",
" <td>74.428571</td>\n",
" <td>67.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Bug</th>\n",
" <th>1</th>\n",
" <td>76.428571</td>\n",
" <td>60.357143</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Psychic</th>\n",
" <th>1</th>\n",
" <td>79.181818</td>\n",
" <td>63.181818</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ground</th>\n",
" <th>1</th>\n",
" <td>81.875000</td>\n",
" <td>86.250000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Rock</th>\n",
" <th>1</th>\n",
" <td>87.500000</td>\n",
" <td>107.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fire</th>\n",
" <th>1</th>\n",
" <td>88.642857</td>\n",
" <td>67.142857</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dragon</th>\n",
" <th>1</th>\n",
" <td>94.000000</td>\n",
" <td>68.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fighting</th>\n",
" <th>1</th>\n",
" <td>102.857143</td>\n",
" <td>61.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fairy</th>\n",
" <th>2</th>\n",
" <td>57.000000</td>\n",
" <td>60.600000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Grass</th>\n",
" <th>2</th>\n",
" <td>57.000000</td>\n",
" <td>65.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ice</th>\n",
" <th>2</th>\n",
" <td>58.750000</td>\n",
" <td>45.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ghost</th>\n",
" <th>2</th>\n",
" <td>60.000000</td>\n",
" <td>60.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Normal</th>\n",
" <th>2</th>\n",
" <td>63.133333</td>\n",
" <td>54.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Electric</th>\n",
" <th>2</th>\n",
" <td>64.714286</td>\n",
" <td>58.857143</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fighting</th>\n",
" <th>2</th>\n",
" <td>65.000000</td>\n",
" <td>65.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Water</th>\n",
" <th>2</th>\n",
" <td>68.111111</td>\n",
" <td>72.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Psychic</th>\n",
" <th>2</th>\n",
" <td>69.285714</td>\n",
" <td>73.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fire</th>\n",
" <th>2</th>\n",
" <td>76.250000</td>\n",
" <td>68.875000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dark</th>\n",
" <th>2</th>\n",
" <td>80.833333</td>\n",
" <td>62.833333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ground</th>\n",
" <th>2</th>\n",
" <td>85.000000</td>\n",
" <td>95.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Bug</th>\n",
" <th>2</th>\n",
" <td>85.416667</td>\n",
" <td>93.750000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Poison</th>\n",
" <th>2</th>\n",
" <td>90.000000</td>\n",
" <td>80.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Steel</th>\n",
" <th>2</th>\n",
" <td>96.666667</td>\n",
" <td>190.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Rock</th>\n",
" <th>2</th>\n",
" <td>109.200000</td>\n",
" <td>99.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Bug</th>\n",
" <th>3</th>\n",
" <td>55.833333</td>\n",
" <td>54.083333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Electric</th>\n",
" <th>3</th>\n",
" <td>57.000000</td>\n",
" <td>54.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ice</th>\n",
" <th>3</th>\n",
" <td>68.571429</td>\n",
" <td>74.285714</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Normal</th>\n",
" <th>3</th>\n",
" <td>69.888889</td>\n",
" <td>57.277778</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Psychic</th>\n",
" <th>3</th>\n",
" <td>70.666667</td>\n",
" <td>60.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Poison</th>\n",
" <th>3</th>\n",
" <td>72.000000</td>\n",
" <td>65.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fighting</th>\n",
" <th>3</th>\n",
" <td>76.000000</td>\n",
" <td>61.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Grass</th>\n",
" <th>3</th>\n",
" <td>77.923077</td>\n",
" <td>56.769231</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Rock</th>\n",
" <th>3</th>\n",
" <td>79.625000</td>\n",
" <td>101.125000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Water</th>\n",
" <th>3</th>\n",
" <td>80.666667</td>\n",
" <td>67.962963</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ghost</th>\n",
" <th>3</th>\n",
" <td>93.000000</td>\n",
" <td>79.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dark</th>\n",
" <th>3</th>\n",
" <td>97.500000</td>\n",
" <td>70.833333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fire</th>\n",
" <th>3</th>\n",
" <td>98.750000</td>\n",
" <td>75.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Steel</th>\n",
" <th>3</th>\n",
" <td>98.750000</td>\n",
" <td>130.833333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ground</th>\n",
" <th>3</th>\n",
" <td>101.428571</td>\n",
" <td>90.714286</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dragon</th>\n",
" <th>3</th>\n",
" <td>113.333333</td>\n",
" <td>95.833333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fairy</th>\n",
" <th>4</th>\n",
" <td>50.000000</td>\n",
" <td>95.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Bug</th>\n",
" <th>4</th>\n",
" <td>62.600000</td>\n",
" <td>70.200000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Water</th>\n",
" <th>4</th>\n",
" <td>72.461538</td>\n",
" <td>67.461538</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Electric</th>\n",
" <th>4</th>\n",
" <td>73.583333</td>\n",
" <td>85.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Poison</th>\n",
" <th>4</th>\n",
" <td>77.166667</td>\n",
" <td>69.833333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Steel</th>\n",
" <th>4</th>\n",
" <td>77.666667</td>\n",
" <td>107.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Normal</th>\n",
" <th>4</th>\n",
" <td>83.055556</td>\n",
" <td>62.722222</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Grass</th>\n",
" <th>4</th>\n",
" <td>84.000000</td>\n",
" <td>80.066667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fire</th>\n",
" <th>4</th>\n",
" <td>85.000000</td>\n",
" <td>68.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ghost</th>\n",
" <th>4</th>\n",
" <td>86.000000</td>\n",
" <td>85.857143</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Rock</th>\n",
" <th>4</th>\n",
" <td>86.500000</td>\n",
" <td>104.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Psychic</th>\n",
" <th>4</th>\n",
" <td>90.000000</td>\n",
" <td>85.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ice</th>\n",
" <th>4</th>\n",
" <td>90.000000</td>\n",
" <td>86.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ground</th>\n",
" <th>4</th>\n",
" <td>104.750000</td>\n",
" <td>112.750000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fighting</th>\n",
" <th>4</th>\n",
" <td>108.333333</td>\n",
" <td>66.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dark</th>\n",
" <th>4</th>\n",
" <td>111.666667</td>\n",
" <td>69.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dragon</th>\n",
" <th>4</th>\n",
" <td>115.000000</td>\n",
" <td>80.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ghost</th>\n",
" <th>5</th>\n",
" <td>41.000000</td>\n",
" <td>87.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Psychic</th>\n",
" <th>5</th>\n",
" <td>52.500000</td>\n",
" <td>65.571429</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Grass</th>\n",
" <th>5</th>\n",
" <td>65.333333</td>\n",
" <td>72.133333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Poison</th>\n",
" <th>5</th>\n",
" <td>72.500000</td>\n",
" <td>72.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Water</th>\n",
" <th>5</th>\n",
" <td>73.277778</td>\n",
" <td>70.277778</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ice</th>\n",
" <th>5</th>\n",
" <td>73.333333</td>\n",
" <td>58.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Bug</th>\n",
" <th>5</th>\n",
" <td>77.611111</td>\n",
" <td>78.277778</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Steel</th>\n",
" <th>5</th>\n",
" <td>81.250000</td>\n",
" <td>102.250000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dark</th>\n",
" <th>5</th>\n",
" <td>81.384615</td>\n",
" <td>71.692308</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Normal</th>\n",
" <th>5</th>\n",
" <td>83.315789</td>\n",
" <td>69.421053</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fire</th>\n",
" <th>5</th>\n",
" <td>87.444444</td>\n",
" <td>60.777778</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Electric</th>\n",
" <th>5</th>\n",
" <td>88.750000</td>\n",
" <td>60.625000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ground</th>\n",
" <th>5</th>\n",
" <td>102.500000</td>\n",
" <td>65.400000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Flying</th>\n",
" <th>5</th>\n",
" <td>107.500000</td>\n",
" <td>75.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fighting</th>\n",
" <th>5</th>\n",
" <td>108.571429</td>\n",
" <td>72.142857</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Rock</th>\n",
" <th>5</th>\n",
" <td>116.000000</td>\n",
" <td>86.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dragon</th>\n",
" <th>5</th>\n",
" <td>129.000000</td>\n",
" <td>90.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Bug</th>\n",
" <th>6</th>\n",
" <td>36.333333</td>\n",
" <td>50.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Flying</th>\n",
" <th>6</th>\n",
" <td>50.000000</td>\n",
" <td>57.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Electric</th>\n",
" <th>6</th>\n",
" <td>50.333333</td>\n",
" <td>47.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Normal</th>\n",
" <th>6</th>\n",
" <td>55.500000</td>\n",
" <td>54.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fairy</th>\n",
" <th>6</th>\n",
" <td>66.222222</td>\n",
" <td>66.444444</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Poison</th>\n",
" <th>6</th>\n",
" <td>67.500000</td>\n",
" <td>75.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Water</th>\n",
" <th>6</th>\n",
" <td>68.000000</td>\n",
" <td>61.800000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fire</th>\n",
" <th>6</th>\n",
" <td>69.375000</td>\n",
" <td>68.250000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dragon</th>\n",
" <th>6</th>\n",
" <td>81.250000</td>\n",
" <td>69.750000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ghost</th>\n",
" <th>6</th>\n",
" <td>81.400000</td>\n",
" <td>89.200000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Grass</th>\n",
" <th>6</th>\n",
" <td>82.200000</td>\n",
" <td>78.400000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Psychic</th>\n",
" <th>6</th>\n",
" <td>82.800000</td>\n",
" <td>65.200000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Rock</th>\n",
" <th>6</th>\n",
" <td>90.333333</td>\n",
" <td>101.111111</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dark</th>\n",
" <th>6</th>\n",
" <td>92.333333</td>\n",
" <td>78.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ice</th>\n",
" <th>6</th>\n",
" <td>93.000000</td>\n",
" <td>134.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Steel</th>\n",
" <th>6</th>\n",
" <td>94.000000</td>\n",
" <td>108.200000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fighting</th>\n",
" <th>6</th>\n",
" <td>99.333333</td>\n",
" <td>71.666667</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" attack defense\n",
"type generation \n",
"Ghost 1 53.750000 53.750000\n",
"Fairy 1 57.500000 60.500000\n",
"Electric 1 62.000000 64.666667\n",
"Ice 1 67.500000 67.500000\n",
"Normal 1 70.625000 56.583333\n",
"Grass 1 72.923077 73.692308\n",
"Water 1 74.193548 83.193548\n",
"Poison 1 74.428571 67.000000\n",
"Bug 1 76.428571 60.357143\n",
"Psychic 1 79.181818 63.181818\n",
"Ground 1 81.875000 86.250000\n",
"Rock 1 87.500000 107.500000\n",
"Fire 1 88.642857 67.142857\n",
"Dragon 1 94.000000 68.333333\n",
"Fighting 1 102.857143 61.000000\n",
"Fairy 2 57.000000 60.600000\n",
"Grass 2 57.000000 65.000000\n",
"Ice 2 58.750000 45.000000\n",
"Ghost 2 60.000000 60.000000\n",
"Normal 2 63.133333 54.000000\n",
"Electric 2 64.714286 58.857143\n",
"Fighting 2 65.000000 65.000000\n",
"Water 2 68.111111 72.500000\n",
"Psychic 2 69.285714 73.000000\n",
"Fire 2 76.250000 68.875000\n",
"Dark 2 80.833333 62.833333\n",
"Ground 2 85.000000 95.000000\n",
"Bug 2 85.416667 93.750000\n",
"Poison 2 90.000000 80.000000\n",
"Steel 2 96.666667 190.000000\n",
"Rock 2 109.200000 99.000000\n",
"Bug 3 55.833333 54.083333\n",
"Electric 3 57.000000 54.000000\n",
"Ice 3 68.571429 74.285714\n",
"Normal 3 69.888889 57.277778\n",
"Psychic 3 70.666667 60.666667\n",
"Poison 3 72.000000 65.333333\n",
"Fighting 3 76.000000 61.000000\n",
"Grass 3 77.923077 56.769231\n",
"Rock 3 79.625000 101.125000\n",
"Water 3 80.666667 67.962963\n",
"Ghost 3 93.000000 79.000000\n",
"Dark 3 97.500000 70.833333\n",
"Fire 3 98.750000 75.000000\n",
"Steel 3 98.750000 130.833333\n",
"Ground 3 101.428571 90.714286\n",
"Dragon 3 113.333333 95.833333\n",
"Fairy 4 50.000000 95.000000\n",
"Bug 4 62.600000 70.200000\n",
"Water 4 72.461538 67.461538\n",
"Electric 4 73.583333 85.500000\n",
"Poison 4 77.166667 69.833333\n",
"Steel 4 77.666667 107.333333\n",
"Normal 4 83.055556 62.722222\n",
"Grass 4 84.000000 80.066667\n",
"Fire 4 85.000000 68.000000\n",
"Ghost 4 86.000000 85.857143\n",
"Rock 4 86.500000 104.333333\n",
"Psychic 4 90.000000 85.000000\n",
"Ice 4 90.000000 86.666667\n",
"Ground 4 104.750000 112.750000\n",
"Fighting 4 108.333333 66.000000\n",
"Dark 4 111.666667 69.000000\n",
"Dragon 4 115.000000 80.000000\n",
"Ghost 5 41.000000 87.000000\n",
"Psychic 5 52.500000 65.571429\n",
"Grass 5 65.333333 72.133333\n",
"Poison 5 72.500000 72.000000\n",
"Water 5 73.277778 70.277778\n",
"Ice 5 73.333333 58.333333\n",
"Bug 5 77.611111 78.277778\n",
"Steel 5 81.250000 102.250000\n",
"Dark 5 81.384615 71.692308\n",
"Normal 5 83.315789 69.421053\n",
"Fire 5 87.444444 60.777778\n",
"Electric 5 88.750000 60.625000\n",
"Ground 5 102.500000 65.400000\n",
"Flying 5 107.500000 75.000000\n",
"Fighting 5 108.571429 72.142857\n",
"Rock 5 116.000000 86.666667\n",
"Dragon 5 129.000000 90.000000\n",
"Bug 6 36.333333 50.000000\n",
"Flying 6 50.000000 57.500000\n",
"Electric 6 50.333333 47.333333\n",
"Normal 6 55.500000 54.500000\n",
"Fairy 6 66.222222 66.444444\n",
"Poison 6 67.500000 75.000000\n",
"Water 6 68.000000 61.800000\n",
"Fire 6 69.375000 68.250000\n",
"Dragon 6 81.250000 69.750000\n",
"Ghost 6 81.400000 89.200000\n",
"Grass 6 82.200000 78.400000\n",
"Psychic 6 82.800000 65.200000\n",
"Rock 6 90.333333 101.111111\n",
"Dark 6 92.333333 78.666667\n",
"Ice 6 93.000000 134.500000\n",
"Steel 6 94.000000 108.200000\n",
"Fighting 6 99.333333 71.666667"
]
},
"execution_count": 106,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"attack_defense_power_over_gens = (pokemon.groupby([\"type\", \"generation\"])[[\"attack\", \"defense\"]].mean().sort_values(by=[\"generation\", \"attack\", \"defense\"]))\n",
"attack_defense_power_over_gens"
]
},
{
"cell_type": "markdown",
"id": "a28d54c9-1aa6-43b8-b4b2-21138ebde142",
"metadata": {},
"source": [
"___\n",
"### Plotting\n",
"Pandas has good plotting capabilities, but using the seaborn library `pip3 install seaborn` has much better capabilities. \n",
"\n",
"Use: `import seaborn as sns`\n",
"\n",
"Set the default theme: `sns.set_theme()`"
]
},
{
"cell_type": "code",
"execution_count": 107,
"id": "923cdfa9-cd08-4031-a956-b84b9f187fb4",
"metadata": {},
"outputs": [],
"source": [
"import seaborn as sns\n",
"sns.set_theme()"
]
},
{
"cell_type": "markdown",
"id": "bfae5881-7334-4aa4-9437-f80f6540b0c5",
"metadata": {},
"source": [
"\n",
"### Histograms\n",
"Good to visualize distribution of a series, puts data inot bins and plots the number of data points in each bin.\n",
"\n",
"Use: `sns.histplot(data=series, xaxis_value, yaxis_value)`"
]
},
{
"cell_type": "code",
"execution_count": 108,
"id": "7b624c32-9e4a-477a-88ac-65d5343f5891",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='generation', ylabel='Count'>"
]
},
"execution_count": 108,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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XwbAOtcFqrfn2GGL1zvYcSNvjybxzOn66yNdlVCiQ+uiJ7bGmLrY9B1IfA4Ev+xiwoSgnJ0czZ87U/fffr6FDh7pNs9lsOnbsWLnH5OXlKTIyskbP63Sasts9+7++0FCrIiLqy+F0qqTE4dFle0rZ/yLt9iK//R9lZaxWi2y28IBeh9pQ1ieHowbbo1H6B6TE4ajWHozKBML26JE+VqaGfaaPVVRJnwOhj4HAm+/RNlt4lfZABWQo+uKLLzRp0iTdfPPNmjRpUrnpsbGx2rp1q0zTdNvdun//fsXHx9f4+UtKPPvLcv2iTMk0/fO4flldpW9Mgf2iD4Z1qA2maVZ7e3QdYvDSNh1I22NN+liZmvaZPlZNZX0OpD4GAl/2MeAOgH7zzTcaO3asunfvrlmzZlU4T+/evZWXl6etW7e6xvbv36+dO3eqd+/etVUqAAAIIH61p6ioqEg5OTmSpKNHj6qgoEDZ2dmSpG7dusk0Td17772qV6+e7rrrLreTpiMiInTVVVdJkrp27arU1FQ9/PDDmjp1qurVq6ennnpKCQkJ6tevX+2vGAAA8Ht+FYpOnjxZ7nBY2f0VK1ZIkutcobvvvtttvm7duulvf/ub6/6CBQs0d+5czZw5UyUlJUpNTdX06dMVEuJXqwwAAPyEXyWEqKgo7d69+5LzVDa9TKNGjTRnzhzNmTPHE6UBAIAgF3DnFAEAAHgDoQgAAECEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAElSiK8LADzJYjFksRgVTrNaLW4/fcXpNOV0mj6tAQBQHqEIQcNiMdS4SQNZLZcOPTZbeC1VVDGH06kzpwsJRgDgZwhFCBoWiyGrxaJV2bv03anCctMNw5DVapHD4ZRp+iaQtGjaQHfe2F4Wi0EoAgA/QyhC0PnuVKGOnigoN24YhkJCrCopcfgsFAEA/BcnWgMAAIhQBAAAIIlQBAAAIIlQBAAAIIlQBAAAIMnPQtHBgwc1c+ZMDRkyRB06dNCgQYMqnO+NN95Q//79lZiYqMGDB2vjxo3l5snPz9fDDz+sbt26qWvXrnrggQf03XffeXsVAABAgPKrULR3717l5OSoTZs2iouLq3CedevWacaMGUpPT1dmZqaSkpI0YcIEffHFF27zTZ48WVu2bNGjjz6qJ598Uvv379eYMWNUUlJSC2sCAAACjV9dpygtLU19+/aVJE2bNk07duwoN88zzzyjgQMHavLkyZKk7t27a8+ePVq8eLEyMzMlSZ9//rk2b96sZcuWKTU1VZIUExOjAQMGaP369RowYEDtrBAAAAgYfrWnyFLJ1zMcPnxYBw4cUHp6utv4gAEDtHXrVl24cEGStGnTJtlsNvXs2dM1T2xsrNq3b69NmzZ5vnAAABDw/GpPUWVyc3Mlle71+bG4uDgVFxfr8OHDiouLU25urmJiYmQY7l8MGhsb61pGTYSEeDZLur7A1FC5mv1FWV2+/jLVSymrzTCMivto/PDTkG/6HBR9rAov97rO9LEyNewzfayiSvocCH0MBP7wpd0BFYry8vIkSTabzW287H7ZdLvdrkaNGpV7fGRkZIWH5C6HxWKoSZOGNVrGxVgtFoWEWL2y7Joq20h9/WWqVWG1XrqPIVbf9TiY+lgV3up1XetjZarbZ/p4eS7W50DqYyDwZR8DKhT5A6fTlN1e/stGayI01KqIiPpyOJ0qKXF4dNme4nA4JUl2e5Hrtr+xWi2y2cLlcFykj0bpm1qJwyH56KvPgqKPVeHlXteZPlamhn2mj1VUSZ8DoY+BoOx37Y0+2mzhVdoDFVChKDIyUlLpx+2bN2/uGrfb7W7TbTabjh07Vu7xeXl5rnlqoqTEs78s1y/KlN9+UWlZXaVvTP79ojdNs8I+unZ7+7DPwdDHqvB2r+tKHytT0z7Tx6qprM+B1MdA4Ms+BtQB0NjYWEkqd15Qbm6uQkNDFR0d7Zpv//795Tbe/fv3u5YBAADwYwEViqKjo9W2bVtlZ2e7jWdlZSklJUVhYWGSpN69eysvL09bt251zbN//37t3LlTvXv3rtWaAQBAYKj24bNRo0Zp/PjxSklJqXD6v//9by1ZskQrVqyo8jKLioqUk5MjSTp69KgKCgpcAahbt25q2rSpJk6cqIceekitW7dWcnKysrKy9OWXX2rlypWu5XTt2lWpqal6+OGHNXXqVNWrV09PPfWUEhIS1K9fv+quMgAACGLVDkUff/yxhg0bdtHpp06d0ieffHJZyzx58qQmTZrkNlZ2f8WKFUpOTtagQYNUVFSkzMxMLV26VDExMVq0aJG6du3q9rgFCxZo7ty5mjlzpkpKSpSamqrp06crJCSgTqMCAAC1pEYJ4VLXjDh48KAaNry8j65HRUVp9+7dlc43bNiwSwYySWrUqJHmzJmjOXPmXFYNAACgbrqsULR27VqtXbvWdT8jI0Ovv/56ufny8/O1e/duzt8BAAAB47JCUVFRkU6fPu26f/bs2Qq/mqNBgwYaPny4fvOb39S8QgAAgFpwWaHozjvv1J133imp9Mtb//jHP6pPnz5eKQwAAKA2Vfucog8//NCTdQAAAPhUjT+KVVBQoG+//VZ2u73CK31ec801NX0KAAAAr6t2KDp16pRmz56t9evXy+Eo/300pmnKMAzt2rWrRgUCAADUhmqHopkzZ2rjxo0aOXKkrr766nLfXA8AABBIqh2KtmzZorvuuku///3vPVkPAACAT1T7u8/q16+vK6+80pO1AAAA+Ey1Q9HgwYO1YcMGT9YCAADgM9U+fNa/f3998sknuvfee3XHHXeoVatWslqt5ebr2LFjjQoEAACoDdUORWUXcZSkjz76qNx0Pn0GAAACSbVD0dy5cz1ZBwAAgE9VOxQNHTrUk3UAAAD4VLVPtAYAAAgm1d5T9Ic//KHSeQzD0Jw5c6r7FAAAALWm2qFo27Zt5cacTqdOnDghh8Ohpk2bKjw8vEbFAQAA1JZqh6IPP/ywwvHi4mK99tpreumll/TCCy9UuzAAAIDa5PFzikJDQ/WrX/1KPXv21J/+9CdPLx4AAMArvHaidbt27fTJJ594a/EAAAAe5bVQ9NFHH3FOEQAACBjVPqdo0aJFFY7n5+frk08+0c6dO3XfffdVuzAAAIDa5PFQFBkZqejoaM2aNUu33357tQsDAACoTdUORV9//bUn6wAAAPAprmgNAACgGuwpKvPxxx/rn//8p7799ltJ0hVXXKHrrrtO3bp1q3FxAAAAtaXaoejChQv67W9/qw0bNsg0TdlsNkmS3W7X8uXLdcMNN2j+/PkKDQ31WLEAAADeUu3DZ4sXL9b777+vX//619q8ebM+/vhjffzxx9qyZYvuuecerV+/XosXL/ZkrQAAAF5T7VD0j3/8Q0OHDtXvf/97/exnP3ONN2vWTL/73e9088036+233/ZIkQAAAN5W7VB04sQJde7c+aLTO3furBMnTlR38Zf0wQcfaNiwYeratatSU1M1adIkHT58uNx8b7zxhvr376/ExEQNHjxYGzdu9Eo9AAD4O4vFUEiIxW//Wa2+/+xXtc8patWqlT7++GONGDGiwumffPKJWrVqVe3CLmbbtm2aMGGCbr75Zk2ZMkVnzpzR008/rXvuuUf/+Mc/VL9+fUnSunXrNGPGDI0bN07du3dXVlaWJkyYoJdffllJSUkerwsAAH9lsRhq3KSBrBbfB49LcTpNGYbhs+evdii6+eabtXDhQjVq1Eh333232rRpI8MwdODAAb300kvKzs7WxIkTPVmrpNKwc8UVV2jOnDmuxjVt2lR33XWXduzYoauvvlqS9Mwzz2jgwIGaPHmyJKl79+7as2ePFi9erMzMTI/XBQCAv7JYDFktFq3K3qXvThX6upwKtWzWUCP6t5PFEoChaNy4cTp8+LBef/11vfHGG7J8nz6dTqdM09TQoUM1btw4jxVapqSkRA0bNnRLko0aNZIkmaYpSTp8+LAOHDig3/3ud26PHTBggJ544glduHBBYWFhHq8NAAB/9t2pQh09UeDrMirkyz1EZaodiqxWq+bNm6e7775bmzZt0tGjRyVJV155pXr37q127dp5rMgfu+WWW/TWW2/p5Zdf1uDBg3XmzBn99a9/VYcOHfSLX/xCkpSbmytJiomJcXtsXFyciouLdfjwYcXFxXmlPgAAEJguKxSdP39ejz/+uH7+859r5MiRkqR27dqVC0ArVqzQq6++qj/+8Y8ev07R1VdfrUWLFum3v/2tHnvsMUlS+/bt9fzzz8tqtUqS8vLyJMl17aQyZffLpldXSIhnj8m6dhUa/pGUK1JWlz+cCHcxZbUZhlFxH40ffhryTZ+Doo9V4eVe15k+VqaGfaaPVVRJn+mjh3xfVtkJ4b5wWaHotdde09q1a5WVlXXJ+a677jr95S9/UXx8vO68884aFfhT//d//6ff//73uv3223XdddfpzJkzWrJkie677z6tWrXKdaK1t1gshpo0aeiVZVstFoWEWL2y7Joqe0HZbOE+rqRyVuul+xhi9V2Pg6mPVeGtXte1Plamun2mj5fnYn2mj55RdhJ4RIR3/45fymWFonfffVf9+vVTdHT0Jedr3bq1brzxRq1bt87joWj27Nnq3r27pk2b5hpLSkrSddddp7feekt33HGHIiMjJUn5+flq3ry5az673S5JrunV4XSasts9e5JaaKhVERH15XA6VVLi8OiyPcXhcEqS7PYi121/Y7VaZLOFy+G4SB+N0je1EodDMmu/PilI+lgVXu51neljZWrYZ/pYRZX0mT56hsNZ2ruCgnMqLvZsjTZbeJX25F1WKNqzZ49uuummKs3btWtXr1wXaN++ferTp4/bWKtWrdSkSRMdOnRIkhQbGyup9Nyisttl90NDQysNdZUpKfHsRu/6RZk/nCzub8rqKn1B+eeLvoxpmhX20bXb24d9DoY+VoW3e11X+liZmvaZPlZNZX2mjx7yfVlOp+mzPl7WQbvi4uIqnyMUGhqqCxcuVKuoS7niiiu0c+dOt7GjR4/q9OnTuvLKKyVJ0dHRatu2rbKzs93my8rKUkpKCp88AwAA5VzWnqIWLVpo7969VZp37969atGiRbWKupThw4drzpw5mj17ttLS0nTmzBllZGSoWbNmSk9Pd803ceJEPfTQQ2rdurWSk5OVlZWlL7/8UitXrvR4TQAAIPBdVijq0aOH3nrrLY0dO1bNmjW76HwnT57UW2+9pf79+9e4wJ8aNWqUwsLC9Morr2jNmjVq2LChkpKStGDBAjVp0sQ136BBg1RUVKTMzEwtXbpUMTExWrRokbp27erxmgAAQOC7rFA0ZswYvf3227rrrrv0+OOPq0uXLuXm2b59u6ZPn67z589r9OjRHiu0jGEYGjFixEW/XuTHhg0bpmHDhnm8BgAAEHwuKxRFR0drwYIFevDBBzV8+HBFR0crPj5eDRs21NmzZ7V3714dOnRI9evX11//+le1bt3aW3UDAAB41GVf0fq6667T22+/rczMTP3zn//Uhg0bXNNatGihYcOGacyYMTX+hBcAAEBtqtbXfERFRWnWrFmSpIKCAp09e1YNGzZURESER4sDAACoLdX+7rMyERERhCEAABDw/PeLWgAAAGoRoQgAAECEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEmEIgAAAEkBHIrWrl2rm2++WYmJiUpOTtbo0aN17tw51/QPP/xQgwcPVmJiovr37681a9b4sFoAAODvQnxdQHVkZGQoMzNT48aNU1JSkk6fPq2tW7fK4XBIkj799FNNmDBBt912mx5++GH9+9//1h//+Ec1bNhQN954o4+rBwAA/ijgQlFubq4WLVqkJUuW6Nprr3WN9+/f33U7IyNDnTt31mOPPSZJ6t69uw4fPqxnnnmGUAQAACoUcIfP3nzzTUVFRbkFoh+7cOGCtm3bVi78DBgwQPv27dORI0dqo0wAABBgAi4Ubd++XfHx8VqyZIlSUlLUqVMnDR8+XNu3b5ckHTp0SMXFxYqNjXV7XFxcnKTSPU0AAAA/FXCHz06cOKEdO3Zoz549euSRRxQeHq5nn31W99xzj9avX6+8vDxJks1mc3tc2f2y6TUREuLZLGmxGKU3DMkwDI8u21PK6rJa/TdHl9VmGEbFfTR++GnIN30Oij5WhZd7XWf6WJka9pk+VlElfaaPHvJ9WRaL4fG/s1UVcKHINE0VFhbq6aefVrt27SRJXbp0UVpamlauXKnU1FSvPr/FYqhJk4ZeWbbVYlFIiNUry66psheUzRbu40oqZ7Veuo8hVt/1OJj6WBXe6nVd62Nlqttn+nh5LtZn+ugZVktpHyMi6vushoALRTabTY0bN3YFIklq3LixOnTooG+++UYDBw6UJOXn57s9zm63S5IiIyNr9PxOpym7vbBGy/ip0FCrIiLqy+F0qqTE4dFle4rD4ZQk2e1Frtv+xmq1yGYLl8NxkT4apW9qJQ6HZNZ+fVKQ9LEqvNzrOtPHytSwz/SxiirpM330DIeztHcFBedUXOzZGm228CrtyQu4UHTVVVfp0KFDFU47f/68WrdurdDQUOXm5qpXr16uaWXnEv30XKPqKCnx7Ebv+kWZpXvC/FFZXaUvKP980ZcxTbPCPrp2e/uwz8HQx6rwdq/rSh8rU9M+08eqqazP9NFDvi/L6TR91kf/PQB6Eddff73OnDmjXbt2ucZOnz6tr776Sh07dlRYWJiSk5P13nvvuT0uKytLcXFxioqKqu2SAQBAAAi4PUV9+/ZVYmKiHnjgAU2ZMkX16tXT0qVLFRYWpjvvvFOSNH78eI0aNUqPPvqo0tPTtW3bNr3zzjt66qmnfFw9AADwVwG3p8hisWjp0qVKSkrSzJkz9eCDDyoiIkIvv/yymjdvLkm6+uqrtXDhQn322We699579c4772j27NlKT0/3cfUAAMBfBdyeIklq2rSp/vKXv1xynj59+qhPnz61VBEAAAh0AbenCAAAwBsIRQAAACIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASAqCUHT27Fn17t1bCQkJ+s9//uM27Y033lD//v2VmJiowYMHa+PGjT6qEgAA+LuAD0VLliyRw+EoN75u3TrNmDFD6enpyszMVFJSkiZMmKAvvvii9osEAAB+L6BD0b59+7Rq1SpNnDix3LRnnnlGAwcO1OTJk9W9e3c99thjSkxM1OLFi31QKQAA8HcBHYpmz56t4cOHKyYmxm388OHDOnDggNLT093GBwwYoK1bt+rChQu1WSYAAAgAIb4uoLqys7O1Z88eLVy4UF999ZXbtNzcXEkqF5bi4uJUXFysw4cPKy4urtrPHRLi2SxpsRilNwzJMAyPLttTyuqyWv03R5fVZhhGxX00fvhpyDd9Doo+VoWXe11n+liZGvaZPlZRJX2mjx7yfVkWi+Hxv7NVFZChqKioSPPmzdOUKVMUERFRbnpeXp4kyWazuY2X3S+bXh0Wi6EmTRpW+/GXYrVYFBJi9cqya6rsBWWzhfu4kspZrZfuY4jVdz0Opj5Whbd6Xdf6WJnq9pk+Xp6L9Zk+eobVUtrHiIj6PqshIENRRkaGmjVrpltvvbXWn9vpNGW3F3p0maGhVkVE1JfD6VRJSfmTxv2Bw+GUJNntRa7b/sZqtchmC5fDcZE+GqVvaiUOh2TWfn1SkPSxKrzc6zrTx8rUsM/0sYoq6TN99AyHs7R3BQXnVFzs2RpttvAq7ckLuFB09OhRvfDCC1q8eLHy8/MlSYWFha6fZ8+eVWRkpCQpPz9fzZs3dz3WbrdLkmt6dZWUeHajd/2iTMk0ffTXuhJldZW+oPzzRV/GNM0K++ja7e3DPgdDH6vC272uK32sTE37TB+rprI+00cP+b4sp9P0WR8DLhQdOXJExcXFuu+++8pNGzVqlLp06aL58+dLKj23KDY21jU9NzdXoaGhio6OrrV6AQBAYAi4UNS+fXutWLHCbWzXrl2aO3euZs2apcTEREVHR6tt27bKzs5W3759XfNlZWUpJSVFYWFhtV02AADwcwEXimw2m5KTkyuc1rFjR3Xs2FGSNHHiRD300ENq3bq1kpOTlZWVpS+//FIrV66szXIBAECACLhQVFWDBg1SUVGRMjMztXTpUsXExGjRokXq2rWrr0sDAAB+KChCUXJysnbv3l1ufNiwYRo2bJgPKgIAAIHGf680BQAAUIsIRQAAACIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASCIUAQAASArAUPTuu+9q/Pjx6t27t5KSkjRkyBCtXr1apmm6zffGG2+of//+SkxM1ODBg7Vx40YfVQwAAAJBwIWiF198UeHh4Zo2bZoyMjLUu3dvzZgxQ4sXL3bNs27dOs2YMUPp6enKzMxUUlKSJkyYoC+++MJ3hQMAAL8W4usCLldGRoaaNm3qup+SkqIzZ85o+fLluv/++2WxWPTMM89o4MCBmjx5siSpe/fu2rNnjxYvXqzMzEwfVQ4AAPxZwO0p+nEgKtO+fXsVFBSosLBQhw8f1oEDB5Senu42z4ABA7R161ZduHChtkoFAAABJOBCUUU+++wztWzZUhEREcrNzZUkxcTEuM0TFxen4uJiHT582BclAgAAPxdwh89+6tNPP1VWVpamTp0qScrLy5Mk2Ww2t/nK7pdNr4mQEM9mSYvFKL1hSIZheHTZnlJWl9Xqvzm6rDbDMCruo/HDT0O+6XNQ9LEqvNzrOtPHytSwz/SxiirpM330kO/LslgMj/+draqADkXHjh3TlClTlJycrFGjRtXKc1oshpo0aeiVZVstFoWEWL2y7Joqe0HZbOE+rqRyVuul+xhi9V2Pg6mPVeGtXte1Plamun2mj5fnYn2mj55htZT2MSKivs9qCNhQZLfbNWbMGDVu3FgLFy6U5ftmRkZGSpLy8/PVvHlzt/l/PL26nE5TdnthjZbxU6GhVkVE1JfD6VRJicOjy/YUh8MpSbLbi1y3/Y3VapHNFi6H4yJ9NErf1EocDsksP7k2BEUfq8LLva4zfaxMDftMH6uokj7TR89wOEt7V1BwTsXFnq3RZguv0p68gAxF586d09ixY5Wfn6/XXntNjRo1ck2LjY2VJOXm5rpul90PDQ1VdHR0jZ+/pMSzG73rF2Wq3PWW/EVZXaUvKP980ZcxTbPCPrp2e/uwz8HQx6rwdq/rSh8rU9M+08eqqazP9NFDvi/L6TR91kf/PQB6ESUlJZo8ebJyc3P1/PPPq2XLlm7To6Oj1bZtW2VnZ7uNZ2VlKSUlRWFhYbVZLgAACBABt6do1qxZ2rhxo6ZNm6aCggK3CzJ26NBBYWFhmjhxoh566CG1bt1aycnJysrK0pdffqmVK1f6rnAAAODXAi4UbdmyRZI0b968ctM++OADRUVFadCgQSoqKlJmZqaWLl2qmJgYLVq0SF27dq3tcgEAQIAIuFD04YcfVmm+YcOGadiwYV6uBgAABIuAO6cIAADAGwhFAAAAIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABIIhQBAABICvJQtG/fPv36179WUlKSevbsqSeeeEIXLlzwdVkAAMAPhfi6AG/Jy8vTXXfdpbZt22rhwoU6fvy45s2bp3PnzmnmzJm+Lg8AAPiZoA1Fr776qs6ePatFixapcePGkiSHw6FZs2Zp7NixatmypW8LBAAAfiVoD59t2rRJKSkprkAkSenp6XI6ndqyZYvvCgMAAH7JME3T9HUR3pCSkqJbb71VDz30kNt4r169NGTIkHLjVWWappxOz7bMMCSLxaKCwgtyeHjZnmK1GIpoECan0+nrUi6JPnoGffQM+ugZ9NEzAqmPnk4mFoshwzAqnS9oD5/Z7XbZbLZy45GRkcrLy6v2cg3DkNVaeWOrI6JBmFeW60kWi//vXKSPnkEfPYM+egZ99Az6WMlz++yZAQAA/EjQhiKbzab8/Pxy43l5eYqMjPRBRQAAwJ8FbSiKjY1Vbm6u21h+fr5OnDih2NhYH1UFAAD8VdCGot69e+ujjz6S3W53jWVnZ8tisahnz54+rAwAAPijoP30WV5engYOHKiYmBiNHTvWdfHGm266iYs3AgCAcoI2FEmlX/Pxpz/9SZ9//rkaNmyoIUOGaMqUKQoL8/+z7wEAQO0K6lAEAABQVUF7ThEAAMDlIBQBAACIUAQAACCJUAQAACCJUAQAACCJUAQAACCJUORTBw8e1MyZMzVkyBB16NBBgwYN8nVJQendd9/V+PHj1bt3byUlJWnIkCFavXq1uBqFZ+Xk5OhXv/qVunfvrk6dOqlPnz6aO3duhd9BCM85e/asevfurYSEBP3nP//xdTlB480331RCQkK5f08++aSvSwtKa9eu1c0336zExEQlJydr9OjROnfuXK3XEVLrzwiXvXv3KicnR126dJHT6eSPtJe8+OKLuvLKKzVt2jQ1adJEH330kWbMmKFjx45pwoQJvi4vaJw5c0adO3fWyJEj1bhxY+3du1cLFy7U3r179cILL/i6vKC1ZMkSORwOX5cRtJ5//nk1atTIdb9ly5Y+rCY4ZWRkKDMzU+PGjVNSUpJOnz6trVu3+mS7JhT5UFpamvr27StJmjZtmnbs2OHjioJTRkaGmjZt6rqfkpKiM2fOaPny5br//vtlsbDD1BOGDBnidj85OVlhYWGaMWOGjh8/zh8TL9i3b59WrVqlqVOn6pFHHvF1OUGpY8eObu8f8Kzc3FwtWrRIS5Ys0bXXXusa79+/v0/q4a+BD/HHuHZU9IbWvn17FRQUqLCw0AcV1R2NGzeWJBUXF/u2kCA1e/ZsDR8+XDExMb4uBaiWN998U1FRUW6ByJf4q4w66bPPPlPLli0VERHh61KCjsPh0Pnz5/XVV19p8eLFSktLU1RUlK/LCjrZ2dnas2ePfvOb3/i6lKA2aNAgtW/fXn369NFzzz3HoUoP2759u+Lj47VkyRKlpKSoU6dOGj58uLZv3+6Tejh8hjrn008/VVZWlqZOnerrUoLS9ddfr+PHj0uSevXqpfnz5/u4ouBTVFSkefPmacqUKQR7L2nevLkmTpyoLl26yDAMffjhh1qwYIGOHz+umTNn+rq8oHHixAnt2LFDe/bs0SOPPKLw8HA9++yzuueee7R+/Xo1a9asVushFKFOOXbsmKZMmaLk5GSNGjXK1+UEpaVLl6qoqEjffPONMjIyNG7cOC1fvlxWq9XXpQWNjIwMNWvWTLfeequvSwlavXr1Uq9evVz3U1NTVa9ePb300ksaN26cWrRo4cPqgodpmiosLNTTTz+tdu3aSZK6dOmitLQ0rVy5UpMmTarVejh8hjrDbrdrzJgxaty4sRYuXMg5XV7Srl07de3aVcOGDdOSJUu0bds2vf/++74uK2gcPXpUL7zwgh544AHl5+fLbre7zo0rLCzU2bNnfVxh8EpPT5fD4dCuXbt8XUrQsNlsaty4sSsQSaXnInbo0EHffPNNrdfDniLUCefOndPYsWOVn5+v1157ze0jtvCehIQEhYaG6tChQ74uJWgcOXJExcXFuu+++8pNGzVqlLp06aLXX3/dB5UBl++qq6666PvD+fPna7kaQhHqgJKSEk2ePFm5ubl6+eWX+Wh4Ldq+fbuKi4s50dqD2rdvrxUrVriN7dq1S3PnztWsWbOUmJjoo8qCX1ZWlqxWqzp06ODrUoLG9ddfrzfffFO7du1S+/btJUmnT5/WV199pbvvvrvW6yEU+VBRUZFycnIkle4SLygoUHZ2tiSpW7duXBvDQ2bNmqWNGzdq2rRpKigo0BdffOGa1qFDB4WFhfmuuCAyYcIEderUSQkJCapfv76+/vprLVu2TAkJCa7rcaHmbDabkpOTK5zWsWNHdezYsZYrCk733nuvkpOTlZCQIEn64IMP9Prrr2vUqFFq3ry5j6sLHn379lViYqIeeOABTZkyRfXq1dPSpUsVFhamO++8s9brMUwuo+wzR44cUZ8+fSqctmLFiou+8eHypKWl6ejRoxVO++CDD9iL4SFLly5VVlaWDh06JNM0deWVV+qGG27QvffeyyekvGzbtm0aNWqUVq9ezZ4iD5k9e7b+9a9/6dixY3I6nWrbtq2GDRumkSNHyjAMX5cXVE6dOqW5c+dq48aNKi4u1tVXX60//OEPuuqqq2q9FkIRAACA+PQZAACAJEIRAACAJEIRAACAJEIRAACAJEIRAACAJEIRAACAJEIRAACAJEIRAHjVm2++qYSEBB05csTXpQCoBKEIADzg2Wef1YYNG3xdBoAa4IrWAOABXbt2Vf/+/TVv3jy3cYfDoZKSEoWFhfH1EICfY08RAPyE0+nU+fPnPbIsq9WqevXqEYiAAEAoAuB127Zt0y233KLExET17dtXr776qhYuXOj6BvIyb731lm655RZ17txZ3bp105QpU/T//t//c5tn5MiRGjRokL755huNHDlSXbp0Ua9evZSZmVnueS9cuKBnnnlGN9xwgzp16qRrr71WTzzxhC5cuOA2X0JCgh577DG9/fbbGjhwoBITE/Wvf/1LkrRs2TINHz5cycnJ6ty5s2655RZlZ2eXe3xhYaHWrl2rhIQEJSQkaNq0aZIufk7Ryy+/rIEDB6pTp05KTU3VrFmzZLfbq72uAGouxNcFAAhuO3fu1OjRo9W8eXNNnDhRTqdTixcvVtOmTd3my8jI0NNPP6309HTddtttOnXqlFauXKlf/vKX+vvf/y6bzeaaNy8vT6NHj9YNN9yg9PR0vffee3ryyScVHx+va6+9VlLp3p7x48frs88+0+233664uDjt2bNHL730kg4cOKAlS5a4Pf+///1vvfvuu/rlL3+pJk2a6Morr5QkrVixQmlpabrppptUXFysdevWadKkSXruued03XXXSZKeeOIJTZ8+XZ07d9btt98uSWrduvVFe7Jw4UItWrRIPXr00IgRI7R//3698sor+s9//qNXXnlFoaGhl7WuADzEBAAvGjt2rNmlSxfz2LFjrrEDBw6YHTp0MOPj403TNM0jR46Y7du3NzMyMtweu3v3brNDhw5u47/61a/M+Ph4c+3ata6x8+fPmz179jQnTpzoGvv73/9utmvXzvzkk0/clvnKK6+Y8fHx5meffeYai4+PN9u1a2fu3bu3XP1FRUVu9y9cuGAOGjTIHDVqlNt4UlKSOXXq1HKPX7NmjRkfH28ePnzYNE3TPHnypNmxY0fznnvuMR0Oh2u+lStXmvHx8ebq1asve10BeAaHzwB4jcPh0NatW9WnTx+1bNnSNd6mTRv16tXLdf/999+X0+lUenq6Tp065fr3s5/9TG3atNG2bdvcltugQQMNGTLEdT8sLEyJiYk6fPiwayw7O1txcXGKjY11W2b37t0lqdwyr7nmGl111VXl1qF+/fqu23l5ecrPz9f//u//aufOndXqyUcffaTi4mKNGjVKFssPb8HDhg1TRESEcnJyLntdAXgGh88AeM3Jkyd17tw5tWnTpty0H48dOHBApmmqX79+FS4nJMT9rapVq1blTlyOjIzU7t27XfcPHjyoffv2KSUl5aK1/VhUVFSF823cuFEZGRnatWuX27lI1T1x+ttvv5UkxcbGuo2HhYUpOjpaR48edRuvyroC8AxCEQCfczqdMgxDmZmZslqt5aY3aNDA7X5F81S0zPj4eP3hD3+ocHqrVq3c7v94j1CZTz/9VOPHj9c111yjRx55RM2bN1doaKjWrFmjd955p9IaPKEq6wrAMwhFALymWbNmqlevng4ePFhu2o/HWrduLdM0FRUVpZiYGI88d+vWrfX1118rJSWl2nt13nvvPdWrV0/Lli1TWFiYa3zNmjXVruuKK66QJOXm5io6Oto1fuHCBR05ckQ9evSo9rIB1AznFAHwGqvVqh49euiDDz7Q8ePHXeMHDx50feRdkvr16yer1apFixbJ/Mn1ZE3T1OnTpy/7udPT03X8+HG9/vrr5aadO3dOhYWFVarfMAw5HA7X2JEjR/TBBx+Um7dBgwblPlJfkR49eig0NFR/+9vf3NZ19erVys/P5xNlgA+xpwiAV02YMEGbN2/WiBEjNGLECDmdTq1cuVI///nPtWvXLkmle3UmT56s+fPn6+jRo+rbt68aNmyoI0eOaMOGDbr99tt17733XtbzDhkyRO+++64eeeQRbdu2Tb/4xS/kcDiUm5ur7OxsPf/880pMTLzkMq699lotX75co0eP1qBBg3Ty5EmtWrVKrVu3LndOT8eOHbV161YtX75cLVq0UFRUlLp06VJumU2bNtXYsWO1aNEijR49Wmlpadq/f79WrVqlxMREDR48+LLWE4DnEIoAeFWnTp2UmZmpJ554Qk8//bT+53/+Rw888IByc3OVm5vrmu++++5T27Zt9eKLL2rx4sWSSs/76dmzp9LS0i77eS0WixYvXqwXX3xRb731lt5//32Fh4crKipKI0eOrNJhupSUFD3++OPKzMzUnDlzFBUVpYceekhHjx4tF4qmTZummTNnasGCBTp37pyGDh1aYSiSpIkTJ6pp06ZauXKl5s6dq8jISN1+++168MEH3a5RBKB28d1nAHzi/vvv1zfffKP169f7uhQAkMQ5RQBqwblz59zuHzhwQJs2bVK3bt18VBEAlMfhMwBe17dvXw0dOtR1HZ5XX31VoaGhGj16tK9LAwAXQhEAr+vVq5fWrVunEydOKCwsTElJSXrwwQfVtm1bX5cGAC6cUwQAACDOKQIAAJBEKAIAAJBEKAIAAJBEKAIAAJBEKAIAAJBEKAIAAJBEKAIAAJBEKAIAAJBEKAIAAJAk/X/tfu4WTRXLngAAAABJRU5ErkJggg==",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#plots a simple graph that counts each genrations pokemon\n",
"sns.histplot(data=pokemon, x=\"generation\")\n"
]
},
{
"cell_type": "code",
"execution_count": 109,
"id": "c9fbe7ee-9775-4db9-bb4a-48ae79cf353b",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='Count', ylabel='attack'>"
]
},
"execution_count": 109,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#using the bins argument to increase / decrease bins\n",
"sns.histplot(data=pokemon, y=\"attack\", bins=5)"
]
},
{
"cell_type": "markdown",
"id": "115abc01-3cbe-4e02-928f-d665956cb0b4",
"metadata": {},
"source": [
"### Barplot\n",
"Good when you want to compare the distribution of a numeric variable across categories, choose one numerica column and one categorical column\n",
"\n",
"Use: `sns.barplot(data=series, xaxis_value, yaxis_value, errorbar=\"sd\"[optional])`"
]
},
{
"cell_type": "code",
"execution_count": 110,
"id": "5986c1ac-6322-4807-ae3a-76b7a8ab9aea",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='special_attack', ylabel='type'>"
]
},
"execution_count": 110,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.barplot(data=pokemon, x=\"special_attack\", y=\"type\", errorbar=None, palette=\"muted\")"
]
},
{
"cell_type": "code",
"execution_count": 111,
"id": "cf8d7b27-74c8-4ef6-90c7-0c0089bc1440",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='attack', ylabel='type'>"
]
},
"execution_count": 111,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.barplot(data=pokemon, x=\"attack\", y=\"type\", errorbar=None)"
]
},
{
"cell_type": "markdown",
"id": "3a0c6081-b82a-479b-9f05-de98b4b5b604",
"metadata": {},
"source": [
"### Scatterplot\n",
"Good to show a relationship between 2 numeric variables. Looking at a point in the example below gives you the y value or speed of a pokemon, tracing it down to the x value or attack gives the attack. Together 1 point will display those 2 values.\n",
"\n",
"Use: `sns.scatterplot(data=series, xvalue, yvalue)`\n",
"\n",
"In the 2nd we are distuingishing categories within the scatter plot using hue. You would want something with a small amount of options. In the pokemon data set I used generation for this, it has 6 options which may be a lot.\n",
"\n",
"Use: `sns.scatterplot(data=series, x=\"column_name\", y=\"column_name\", hue=\"column_name\", alpha=int, s=int)`\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 112,
"id": "590531f5-8c8d-46b9-805f-38506139c59c",
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='attack', ylabel='speed'>"
]
},
"execution_count": 112,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.scatterplot(data=pokemon, x=\"attack\", y=\"speed\")"
]
},
{
"cell_type": "code",
"execution_count": 113,
"id": "06473221-6c5d-4808-8f32-4562d79fd3d4",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='defense', ylabel='special_attack'>"
]
},
"execution_count": 113,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.scatterplot(data=pokemon, x=\"defense\", y=\"special_attack\", hue=\"generation\", alpha=0.5, s=60)"
]
},
{
"cell_type": "markdown",
"id": "32c3d7cd-b8a0-4135-94f3-6d0816e2f154",
"metadata": {},
"source": [
"### relplot()\n",
"Lets you plot across multiple categories and make several plots at once. \n",
"\n",
"You use an x and y parameter as usual, but there also is a `col` paraemeter which allows you to add different columns of charts. In the first example we are plotting the attack and speed variables, we are using `col=\"legendary\"` to see how legendary vs non legendary pokemon's attack and speed values relate.\n",
"\n",
"Use: `sns.relplot(data=series, x=\"xvalue\", y=\"yvalue\", col=\"another_column\")`\n",
"\n",
"In the 2nd example we are accessing values inside a column, instead of a full column.\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 118,
"id": "185b11c9-9138-46ef-b995-ae6e92178f1f",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/cooperl/.local/lib/python3.10/site-packages/seaborn/axisgrid.py:118: UserWarning: The figure layout has changed to tight\n",
" self._figure.tight_layout(*args, **kwargs)\n"
]
},
{
"data": {
"text/plain": [
"<seaborn.axisgrid.FacetGrid at 0x7ff1cddf9210>"
]
},
"execution_count": 118,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1000x500 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.relplot(data=pokemon, x=\"speed\", y=\"attack\", col=\"legendary\")"
]
},
{
"cell_type": "code",
"execution_count": 117,
"id": "a1007818-d79c-48bb-bb6b-a4a25aa93948",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/cooperl/.local/lib/python3.10/site-packages/seaborn/axisgrid.py:118: UserWarning: The figure layout has changed to tight\n",
" self._figure.tight_layout(*args, **kwargs)\n"
]
},
{
"data": {
"text/plain": [
"<seaborn.axisgrid.FacetGrid at 0x7ff1ce025150>"
]
},
"execution_count": 117,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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"text/plain": [
"<Figure size 1595.72x500 with 3 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fav_types = pokemon[pokemon.type.isin([\"Fighting\", \"Ghost\", \"Grass\"])]\n",
"sns.relplot(data=fav_types, x=\"hp\", y=\"speed\", hue=\"legendary\", col=\"type\", s=100)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2423783a-2345-4ce1-b47c-2625e50baeaa",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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